Urban areas are associated with higher depression risks than rural areas. However, less is known about how different types of urban environments relate to depression risk. Here, we use satellite imagery and machine learning to quantify three-dimensional (3D) urban form (i.e., building density and height) over time. Combining satellite-derived urban form data and individual-level residential addresses, health, and socioeconomic registers, we conduct a case-control study ( n = 75,650 cases and 756,500 controls) to examine the association between 3D urban form and depression in the Danish population. We find that living in dense inner-city areas did not carry the highest depression risks. Rather, after adjusting for socioeconomic factors, the highest risk was among sprawling suburbs, and the lowest was among multistory buildings with open space in the vicinity. The finding suggests that spatial land-use planning should prioritize securing access to open space in densely built areas to mitigate depression risks.

中文翻译：

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在丹麦，中密度城市比高密度城市的抑郁风险更高

与农村地区相比，城市地区的抑郁风险更高。然而，人们对不同类型的城市环境与抑郁风险的关系知之甚少。在这里，我们使用卫星图像和机器学习来量化随时间变化的三维 (3D) 城市形态（即建筑密度和高度）。结合卫星衍生的城市形态数据和个人层面的居住地址、健康和社会经济登记，我们进行了病例对照研究（n= 75,650 例和 756,500 例对照）以检查丹麦人口中 3D 城市形态与抑郁症之间的关联。我们发现，居住在人口稠密的市中心地区并没有带来最高的抑郁风险。相反，在调整社会经济因素后，风险最高的是广阔的郊区，最低的是附近有空地的多层建筑。该发现表明，空间土地利用规划应优先考虑确保进入密集建筑地区的开放空间，以减轻萧条风险。