医学
归一化差异植被指数
逻辑回归
优势比
心理健康
效果修正
环境卫生
人口学
置信区间
精神科
内科学
生态学
叶面积指数
生物
社会学
作者
Can Yang,Jing Wang,Haijun Yang,Jianpeng Liao,Xiaodie Wang,Kuizhuang Jiao,Xuxi Ma,Jingling Liao,Xingyuan Liu,Lu Ma
标识
DOI:10.1016/j.jpsychires.2022.11.014
摘要
Air pollution is a risk factor for increased hospital admissions due to mental disorders, while green spaces have been linked with better mental health. We linked daily hospital admission records from Wuhan's 74 municipal hospitals from 2017 to 2019 with modeled annual average NO2 concentrations and added data on the residential surrounding green spaces with 250 m and 500 m buffers based on the normalized difference vegetation index (NDVI) using a land use regression model (LUR). The conditional logistic regression model was used to estimate the acute effect of short-term NO2 exposure, and stratification analyses were applied to explore the modification effect of long-term NO2 exposure and green spaces by estimating the odds ratios in the single- and dual-environmental factor groups. A total of 42,705 hospital admissions for mental disorders were identified. Short-term exposure to NO2 was associated with an increased risk of hospital admission for mental disorders. A 10 μg/m3 increase in NO2 (lag01 day) was associated with an increase in hospital admissions of 2.86% (95% CI, 2.05-3.68) for the total mental disorders. Compared with patients in the "low-NDVI/low-NO2" group (ER = 2.27%, 95% CI, 0.27-4.31), patients in the "high-NDVI/low-NO2" group (ER = 1.93%, -0.10-3.99) showed a lower and insignificant increase in hospitalizations for the total mental disorders, while greenness had a slight moderating effect in the high-level long-term NO2 exposure areas. This study suggested that green spaces may moderate the acute effect of NO2 exposure for mental disorder hospitalizations, especially in low-level long-term NO2 exposure areas.
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