Neighborhood Looking Glass: 360 Degree Automated Characterization of the Built Environment for Neighborhood Effects Research

Neighborhood Looking Glass：用于邻里效应研究的建筑环境的 360 度自动表征

• 批准号: 9979947
• 负责人: QUYNH NGUYEN
• 金额: $ 32.97万
• 依托单位: UNIV OF MARYLAND, COLLEGE PARK
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-06 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9979947
• 关键词: Accounting; Alcohol or Other Drugs use; Algorithms; Bioinformatics; Biological; Characteristics; Chronic; Chronic Disease; Cities; Collection; Communities; Community Health; Computer Vision Systems; Consumption; Data; Data Collection; Data Sources; Development; Disease; Environment; Environmental Risk Factor; Epidemic; Epidemiology; Face; Family; Food; Food Access; Geographic Information Systems; Geography; Glass; Grant; Happiness; Health; Health Food; Health Personnel; Health behavior; Health care facility; Healthcare; Image; Individual; Informatics; Investigation; Label; Literature; Manuals; Measures; Medical Records; Mental Health; Methods; Nature; Neighborhoods; Obesity; Outcome; Overdose; Patients; Physical activity; Physical environment; Premature Mortality; Process; Public Health; Quality Indicator; Research; Research Personnel; Resources; Risk; Sampling; Signal Transduction; Site Visit; Social Environment; Social Processes; Source; Structure; Substance abuse problem; System; Techniques; Testing; Time; United States; Visit; built environment; burden of illness; cardiovascular disorder risk; cohort; computer science; contextual factors; convolutional neural network; cost; crowdsourcing; data management; data mining; data resource; data sharing; data visualization; data warehouse; density; health care availability; health disparity; improved; land use; obesity risk; object recognition; physical conditioning; population based; social; social media; walkability; young adult

PROJECT SUMMARY/ABSTRACT This proposal represents a vertical advancement in neighborhood effects research, producing for the first time, national neighborhood indicators of the built environment. Thus far, only local studies have been conducted due to the resource-intensive nature of site visits to conduct assessments of community features and also manual annotations of street images. With the recent advancement of computer vision and the emergence of massive sources of image data, we will leverage our team’s abilities to develop a data collection strategy utilizing geographic information systems to assemble a national collection of Google Street View images of all road intersections and street segments in the United States. We will utilize this data bank, and develop informatics algorithms to produce neighborhood summaries of built environment that have been theoretically and empirically identified to be important for health outcomes. After the creation of Neighborhood Looking Glass, we will conduct investigations into the impact of neighborhood environments on health utilizing medical records from hundreds of thousands of patients and accounting for predisposing characteristics in analyses. Our investigative team—comprised of experts in the field of epidemiology, computer vision, bioinformatics, and computer science—is uniquely suited to implement the study aims. Our Specific Aims are: 1) Develop informatics techniques to produce neighborhood quality indicators; 2) Measure the accuracy of data algorithms and construct an interactive geoportal for neighborhood data visualization and data sharing, 3) Utilize Neighborhood Looking Glass and a large collection of medical records from Intermountain Healthcare to investigate neighborhood influences on the risk of obesity and substance abuse. The epidemic rise in chronic health conditions is recent and as such suggests its cause is social, cultural, and constructed rather than purely biological. Thus, we have the possibility of intervening on the environment to better support health. Recent studies suggest that the current cohort of young adults may face historically high cardiovascular disease risk and chronic disease burden. Our substantive investigation of the impact of neighborhood factors on chronic conditions will contribute further to the understanding of contextual influences on the health of this cohort at the forefront of a chronic disease epidemic. Moreover, the dramatic rise in overdoses, accidental poisonings, and mental health issues contributing to premature mortality warrants further investigation into risk-inducing environmental factors for substance abuse. Neighborhood Looking Glass will be a significant benefit to neighborhood effects researchers, harnessing the largely untapped potential of street image data to capture built environment characteristics. Results can be utilized to inform population-based strategies to reduce health disparities and improve health.

项目总结/摘要 这一提议代表了邻里效应研究的纵向进步，为 第一次，国家建成环境邻里指标。到目前为止，只有当地的研究 由于实地访问需要大量资源， 社区特征以及街道图像的手动注释。随着最近的进步， 计算机视觉和大量图像数据源的出现，我们将利用我们团队的 有能力利用地理信息系统制定数据收集战略， 全国收集的谷歌街景图像的所有道路交叉口和街道路段， 美国的我们将利用这个数据库，并开发信息学算法，以产生 已在理论和经验上确定的建成环境的邻里摘要 to be important重要for health健康outcomes结果.在创建邻里展望玻璃后，我们将 利用医疗手段调查社区环境对健康的影响 来自数十万患者的记录， 分析。我们的调查团队由流行病学、计算机视觉、 生物信息学和计算机科学是唯一适合实现研究目标。我们的具体 目的是：1）发展信息技术，以产生邻里质量指标; 2）测量 数据算法的准确性，并为邻域数据构建交互式地理门户 可视化和数据共享，3）利用邻里玻璃和大量的 Intermountain Healthcare的医疗记录，以调查邻里对 肥胖和药物滥用。慢性病流行率上升是最近的事， 表明其原因是社会的，文化的，而不是纯粹的生物学。因此，我们有 干预环境以更好地支持健康的可能性。最近的研究表明， 目前的年轻人群体可能面临历史上较高的心血管疾病风险和慢性 疾病负担。我们对社区因素对慢性病影响的实质性调查 条件将有助于进一步了解上下文对健康的影响， 处于慢性病流行前沿的人群。此外，药物过量的急剧上升， 意外中毒和心理健康问题导致过早死亡， 调查导致药物滥用的危险环境因素。邻里关系 玻璃将是邻里效应研究人员的一个重大利益， 未开发的潜力，街道图像数据，以捕捉建筑环境的特点。结果可 用于为减少健康差距和改善健康的基于人口的战略提供信息。