2014-2019年华盛顿特区社区建筑环境和慢性健康状况的变化:纵向分析
Quynh C Nguyen1, Riki Doumbia2, Thu T Nguyen3
1National Institute of Nursing Research, National Institutes of Health, Bethesda, MD, United States.
JMIR formative research
|December 10, 2025
概括
谷歌街景 (GSV) 和计算机视觉显示了华盛顿特区的城市变革. 发展与改善的健康结果相关,但公平的进步需要进一步调查.
科学领域:
- 城市规划和公共卫生研究.
- 利用地理空间技术和深度学习进行环境健康研究.
背景情况:
- 传统的社区研究通常使用横截面设计.
- 谷歌街景 (GSV) 图像提供可扩展的纵向数据,用于建筑环境评估.
研究的目的:
- 分析2014-2019年华盛顿特区建筑环境和人口统计数据的纵向变化.
- 使用GSV和计算机视觉检查这些变化与健康结果之间的关联.
主要方法:
- 系统地采集了434,115张GSV图像,每隔100米间进行采样.
- 建筑环境特征提取的卷积神经网络 (CNN).
- 多层混合效应模型来评估建筑环境与健康结果的关联.
主要成果:
- 转向更高密度的住房 (66%-72%) 和单车道 (37%-42%).
- 城市化指的是大学受过教育的居民 (16%-41%),收入和财产价值的增加.
- 增加的建筑与较低的肥胖,糖尿病,高胆固醇和癌症率有关;较高的非裔美国人社区的建筑较少.
结论:
- 华盛顿特区经历了人口统计学转变的重大城市转型.
- 城市发展与慢性疾病流行率的降低有关.
- 强调城市发展,人口统计和健康的复杂相互作用,需要进一步研究社区影响.
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