Peng Wenjia, Shi Hengyuan, Li Mengying, Li Xinghui, Liu Ting, Wang Ying
School of Public Health, Fudan University, Shanghai, People's Republic of China.
Epidemiology and Health Statistics, School of Public Health, Bengbu Medical College, Bengbu, Anhui, People's Republic of China.
Environ Sci Pollut Res Int. 2022 Feb;29(8):12054-12064. doi: 10.1007/s11356-021-16585-5. Epub 2021 Sep 24.
Residential greenness exposure has been linked to a number of physical and mental disorders. Nevertheless, evidence on the association between greenness and geriatric depression was limited and focused on developed countries. This study was aimed to investigate whether the relationship between residential greenness exposure and geriatric depression exists among the elderly with long-term care insurance (LTCI) in Shanghai, China. In 2018, a total of 1066 LTCI elderly from a cross-sectional survey completed a questionnaire in Shanghai. Residential greenness indicators, including normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI), were calculated from the Landsat 8 imagery data in different buffers (100-m, 300-m, and 500-m). Mediation analysis by perceived social support was conducted to explore potential mechanisms underlying the associations. In the fully adjusted model, one IQR increase of NDVI and SAVI in the 300-m buffer size was associated with an 11.9% (PR: 0.881, 95% CI: 0.795, 0.977) and 14.7% (PR: 0.853, 95% CI: 0.766, 0.949) lower prevalence of geriatric depression, respectively. Stronger association was observed in the elderly with lower education level, living in non-central area, and lower family monthly income. Perceived social support significantly mediated 40.4% of the total effect for NDVI 300-m buffer and 40.3% for SAVI 300-m buffer to the greenness-depression association, respectively. Our results indicate the importance of residential greenness exposure to geriatric depression, especially for the elderly with lower education level, living in non-central area, and lower family monthly income. Perceived social support might mediate the association. Well-designed longitudinal studies are warranted to confirm our findings and investigate the underlying mechanisms.
居住环境的绿化程度与多种身心疾病有关。然而，关于绿化程度与老年抑郁症之间关联的证据有限，且主要集中在发达国家。本研究旨在调查在中国上海参加长期护理保险（LTCI）的老年人中，居住环境绿化程度与老年抑郁症之间是否存在关联。2018年，来自上海一项横断面调查的1066名参加LTCI的老年人完成了一份问卷。利用不同缓冲距离（100米、300米和500米）的陆地卫星8号影像数据计算了居住环境绿化指标，包括归一化植被指数（NDVI）和土壤调节植被指数（SAVI）。通过感知社会支持进行中介分析，以探索这些关联背后的潜在机制。在完全调整模型中，300米缓冲距离下NDVI和SAVI每增加一个四分位距，老年抑郁症患病率分别降低11.9%（PR：0.881，95%CI：0.795，0.977）和14.7%（PR：0.853，95%CI：0.766，0.949）。在教育水平较低、居住在非中心区域且家庭月收入较低的老年人中观察到更强的关联。感知社会支持分别显著介导了NDVI 300米缓冲距离与绿化-抑郁关联总效应的40.4%和SAVI 300米缓冲距离与绿化-抑郁关联总效应的40.3%。我们的结果表明居住环境绿化程度对老年抑郁症很重要，特别是对于教育水平较低、居住在非中心区域且家庭月收入较低的老年人。感知社会支持可能介导了这种关联。有必要开展精心设计的纵向研究来证实我们的发现并探究潜在机制。
