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Impact of Different Greenspace Metrics on Cardiovascular Disease Incidence in Urban Settings: A Comparative Analysis

delete2025-03-01
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PRE
AI
D
Dong, Ruoyu
袁宏 (Yuan Hong)
G
Gang Xu
Y
Yuchen Li
Y
Yanqing Xu
C
Cong Fu *
DOI:10.1007/s11524-025-00971-2delete
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Abstract

Abstract

En 中文
Cardiovascular diseases (CVDs) are the leading cause of global mortality, and urban greenspace can reduce CVDs risk. However, the evidence relating various greenspace metrics to CVDs risk is inconclusive. To enhance the understanding of the correlation between greenspace and CVDs, we compared three greenspace indicators-street view-based greenspace (SVG), normalized difference vegetation index (NDVI), and green cover rate (GCR). We used a large sample of 36,504 CVDs hospitalization records with precise residential addresses from 2017 to 2022 in Jingzhou, China. Employing the geographically weighted regression (GWR) model, we investigated the association between greenspace and CVDs incidence at the population level. We found significant negative associations between NDVI/SVG and CVDs incidence (SVG: beta = - 1.64; 95% CI, [- 2.12, - 1.15]; NDVI: beta = - 8.57; 95% CI, [- 9.81, - 7.33]), with NDVI exhibiting a more substantial protective effect. However, no significant relationship was found in GCR (p = 0.161). The impacts varied by age, but not by gender, with younger individuals benefiting more than the elderly, and SVG showed no significant relationship with CVDs incidence in individuals over 65 years. Our findings suggested the importance of the presence of greenspace in CVDs prevention. Consequently, in urban greenspace planning, priority should be given to the vegetation quantity in residential areas over the size of greenspace facilities located distant from residences.
Keywords:
Cardiovascular diseases
Greenspace
NDVI
Street view greenness
Green cover

Journal

J
Journal of Urban Health and Bulletin of the New York Academy of Medicine
IF:
4.1
Papers:
2.4K
Citations:
5.8K

Organization

Y
Yangtze University
Scholars:
8.8K
Papers: 5.2K
Citations: 6.5K
U
university of leeds
Scholars:
3.5W
Papers: 3.3W
Citations: 45
W
wuhan university
Scholars:
7.8W
Papers: 5.7W
Citations: 70
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