Hu Kejia, Wang Shiyi, Fei Fangrong, Fu Jingqiao, Shen Yujie, Chen Feng, Zhang Yunquan, Cheng Jian, Yang Xuchao, Zhong Jieming, Guo Yuming, Wu Jiayu
Center of Clinical Big Data and Analytics of the Second Affiliated Hospital and School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
Zhejiang Key Laboratory of Intelligent Preventive Medicine, Hangzhou, China.
Environ Health Perspect. 2025 May;133(5):57012. doi: 10.1289/EHP14014. Epub 2025 May 22.
Green and blue spaces (GBS) are assumed to mitigate heat-induced health risks. However, few studies have explored the impact of type-specific GBS changes on heat-related mortality burden.
This study aimed to investigate the effect modifications of different GBS types on heat-related mortality risks, and to estimate the changes in mortality burden in multiple GBS scenarios.
A case time-series study design was utilized based on the daily data on all-cause mortality and temperatures from 2009 to 2020 in 1,085 subdistricts in China. Mortality count data were obtained from the Zhejiang Center for Disease Control and Prevention. Meteorological data on temperature and relative humidity were acquired from the Zhejiang Meteorological Bureau. GBS exposure was assessed by integrating fine-scale population density, GBS boundary from Baidu and OpenStreetMap, and street-view image data from Baidu. Conditional Poisson regression analyses were conducted with the distributed lag nonlinear model, incorporating modifiers of type-specific GBS exposure. Changes in heat-attributable mortality under different GBS scenarios were also assessed.
Heat-related mortality risks were lower for populations with high exposure (95%) than for those with low exposure (5%) ) to overall green spaces, forests, parks, nature reserves, and street greenery, rather than to grasses, farms, and scrubs; and ) to overall blue spaces, lakes, and rivers, rather than reservoirs, wetlands, or coasts. Increases of 10%, 20%, and 30% exposure to overall green spaces are expected to avoid heat-related mortality burden by 1.6% [95% empirical confidence interval (eCI): 1.4, 1.9, 3.2% (95% eCI: 2.5, 3.9), and 4.8% (95% eCI: 3.5, 6.2)], respectively, whereas corresponding estimates for overall blue spaces are 5.4% (95% eCI: 4.4, 6.4), 10.8% (95% eCI: 8.5, 13.3), and 16.2% (95% eCI: 12.3, 20.5), respectively. Conversely, a 30% decrease in overall green space exposure and overall blue space exposure will increase the heat-related mortality burden by 4.8% (95% eCI: 4.3, 5.2) and 15.9% (95% eCI: 15.2, 16.7), respectively.
Our study revealed differences in the capacity of various GBS types to mitigate heat-related mortality risks. While the protective effects of GBS may be moderate, targeted planning strategies should prioritize their implementation for maximum benefits in mitigating heat-related health risks. The continuous shrinkage of the GBS would render other efforts futile, such as heat-health action plans. https://doi.org/10.1289/EHP14014.
绿色和蓝色空间（GBS）被认为可以减轻高温引发的健康风险。然而，很少有研究探讨特定类型的GBS变化对与高温相关的死亡负担的影响。
本研究旨在调查不同类型的GBS变化对与高温相关的死亡风险的影响，并估计多种GBS情景下的死亡负担变化。
采用病例时间序列研究设计，基于2009年至2020年中国1085个街道的全因死亡率和温度的每日数据。死亡计数数据来自浙江省疾病预防控制中心。温度和相对湿度的气象数据从浙江省气象局获取。通过整合精细尺度的人口密度、来自百度和OpenStreetMap的GBS边界以及来自百度的街景图像数据来评估GBS暴露。使用分布滞后非线性模型进行条件泊松回归分析，纳入特定类型GBS暴露的修正因素。还评估了不同GBS情景下与高温相关的死亡率变化。
与低暴露（5%）于总体绿地、森林、公园、自然保护区和街道绿化的人群相比，高暴露（95%）于这些区域的人群与高温相关的死亡风险更低，而低暴露于草地、农场和灌木丛的人群则不然；与低暴露于水库、湿地或海岸相比，高暴露于总体蓝色空间、湖泊和河流的人群与高温相关的死亡风险更低。预计总体绿地暴露增加10%、20%和30%，分别可避免1.6%[95%经验置信区间（eCI）：1.4，1.9]、3.2%（95% eCI：2.5，3.9）和4.8%（95% eCI：3.5，6.2）的与高温相关的死亡负担，而总体蓝色空间的相应估计分别为5.4%（95% eCI：4.4，6.4）、10.8%（95% eCI：8.5，13.3）和16.2%（95% eCI：12.3，20.5）。相反，总体绿地暴露和总体蓝色空间暴露减少30%，将分别使与高温相关的死亡负担增加4.8%（95% eCI：4.3，5.2）和15.9%（95% eCI：15.2，16.7）。
我们的研究揭示了不同类型的GBS减轻与高温相关的死亡风险的能力存在差异。虽然GBS的保护作用可能是适度的，但有针对性的规划策略应优先实施，以在减轻与高温相关的健康风险方面获得最大效益。GBS的持续缩减将使其他努力徒劳无功，如高温健康行动计划。https://doi.org/10.1289/EHP14014
