Zhang Ting, Huang Bo, Yan Yizhen, Lin Yinyi, Wong Hung, Wong Samuel Yeung-Shan, Chung Roger Yat-Nork
School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai, 200030, China; Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, 999077, China.
Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, 999077, China; Department of Geography and Resource Management, The Chinese University of Hong Kong, Hong Kong, 999077, China; Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, 518057, China.
Int J Hyg Environ Health. 2023 Apr;249:114145. doi: 10.1016/j.ijheh.2023.114145. Epub 2023 Feb 26.
Residential greenness was theoretically associated with health-related consumption behaviors concerning the socio-ecological model and restoration environment theory, but empirical studies were limited, especially in high-density cities. We examined the associations of residential greenness with unhealthy consumption behaviors (infrequent breakfast consumption, infrequent fruit consumption, infrequent vegetable consumption, alcohol drinking, binge drinking, cigarette smoking, moderate-to-heavy smoking, and heavy smoking) using street-view and conventional greenness metrics in high-density Hong Kong.
This cross-sectional study employed survey data from 1,977 adults and residence-based objective environmental data in Hong Kong. Street-view greenness (SVG) was extracted from Google Street View images using an object-based image classification algorithm. Two conventional greenness metrics were used, including normalized difference vegetation index (NDVI) derived from Landsat 8 remote-sensing images and park density derived from a geographic information system database. In the main analyses, logistic regression analyses together with interaction and stratified models were performed with environmental metrics measured within a 1000-m buffer of residence.
A standard deviation higher SVG and NDVI were significantly associated with fewer odds of infrequent breakfast consumption (OR = 0.81, 95% CI 0.71-0.94 for SVG; OR = 0.83, 95% CI 0.73-0.95 for NDVI), infrequent fruit consumption (OR = 0.85, 95% CI 0.77-0.94 for SVG; OR = 0.85, 95% CI 0.77-0.94 for NDVI), and infrequent vegetable consumption (OR = 0.78, 95% CI 0.66-0.92 for SVG; OR = 0.81, 95% CI 0.69-0.94 for NDVI). The higher SVG was significantly associated with less binge drinking and the higher SVG at a 400-m buffer and a 600-m buffer were significantly associated with less heavy smoking. Park density was not significantly associated with any unhealthy consumption behaviors. Some of the above significant associations were moderated by moderate physical activity, mental and physical health, age, monthly income, and marital status.
This study highlights the potential beneficial impact of residential greenness, especially in terms of street greenery, on healthier eating habits, less binge drinking, and less heavy smoking.
根据社会生态模型和恢复环境理论，居住环境的绿化在理论上与健康相关的消费行为有关，但实证研究有限，尤其是在高密度城市。我们利用街景和传统绿化指标，在高密度的香港研究了居住环境绿化与不健康消费行为（很少吃早餐、很少吃水果、很少吃蔬菜、饮酒、暴饮、吸烟、中度至重度吸烟和重度吸烟）之间的关联。
这项横断面研究采用了来自1977名成年人的调查数据以及香港基于住所的客观环境数据。使用基于对象的图像分类算法从谷歌街景图像中提取街景绿化（SVG）。使用了两个传统绿化指标，包括从Landsat 8遥感图像得出的归一化植被指数（NDVI）和从地理信息系统数据库得出的公园密度。在主要分析中，采用逻辑回归分析以及交互作用和分层模型，对在住所1000米缓冲区内测量的环境指标进行分析。
SVG和NDVI每增加一个标准差，很少吃早餐（SVG的OR = 0.81，95%CI 0.71 - 0.94；NDVI的OR = 0.83，95%CI 0.73 - 0.95）、很少吃水果（SVG的OR = 0.85，95%CI 0.77 - 0.94；NDVI的OR = 0.85，95%CI 0.77 - 0.94）和很少吃蔬菜（SVG的OR = 0.78，95%CI 0.66 - 0.92；NDVI的OR = 0.81，95%CI 0.69 - 0.94）的几率显著降低。较高的SVG与较少的暴饮显著相关，在400米缓冲区和600米缓冲区较高的SVG与较少的重度吸烟显著相关。公园密度与任何不健康消费行为均无显著关联。上述一些显著关联受到适度体育活动、身心健康、年龄、月收入和婚姻状况的调节。
本研究强调了居住环境绿化，尤其是街道绿化，对更健康的饮食习惯、较少的暴饮和较少的重度吸烟可能产生的有益影响。
