Zhou Wensu, Wang Qiong, Kadier Aimulaguli, Wang Wenjuan, Zhou Fenfen, Li Rui, Ling Li
Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Environ Res. 2023 Jan 15;217:114854. doi: 10.1016/j.envres.2022.114854. Epub 2022 Nov 18.
Few studies have investigated the effects of greenness exposure, green land cover types and diversity and their interaction with particulate matter (PM) to adiposity.
Cohort data were collected from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Baseline data on greenness levels, green land cover types and diversity were assessed by the Normalized Difference Vegetation Index (NDVI), three greenery types (trees, shrublands and grassland) and Shannon's diversity index, respectively. Body mass index (BMI) and waist circumference (WC) were separately used as dependent variables and represented for peripheral overweight/obesity and central obesity, respectively. The mixed Cox model with random intercept was used to estimate the effects of greenness levels, types and diversity on overweight/obesity using single and multiple exposure models. We also examined the interaction of PM and the aforementioned indicators on overweight/obesity on both additive and multiplicative scales.
Single exposure models showed that higher levels of residential greenness, tree coverage and ratio of trees to shrublands/grassland were inversely associated with peripheral overweight/obesity and central obesity. An increase in shrublands, grassland and diversity of green was related to lower odds of peripheral overweight/obesity. Multiple exposure models confirmed the association between greenness levels and peripheral overweight/obesity. Males, educated participants and elderly who lived in southern regions and areas with cleaner air environments acquired more benefits from greenspace exposure. Single and multiple exposure models indicated that an antagonistic effect of increasing PM and decreasing greenness levels on peripheral overweight/obesity and central obesity. Single exposure models showed the potential interaction of tree coverage, ratio of trees to grassland and PM exposures on the risk of peripheral overweight/obesity.
Increasing residential greenness and diversity of green were associated with healthy weight status. The relationship between greenery and overweight/obesity varied, and the effects of greenspace exposure on overweight/obesity were associated with air pollution.
很少有研究调查绿色环境暴露、绿地覆盖类型和多样性及其与颗粒物（PM）对肥胖的相互作用。
从中国老年健康影响因素跟踪调查（CLHLS）中收集队列数据。分别通过归一化植被指数（NDVI）、三种绿化类型（树木、灌木丛和草地）和香农多样性指数评估绿色程度、绿地覆盖类型和多样性的基线数据。体重指数（BMI）和腰围（WC）分别用作因变量，分别代表外周超重/肥胖和中心性肥胖。使用具有随机截距的混合Cox模型，通过单暴露模型和多暴露模型估计绿色程度、类型和多样性对超重/肥胖的影响。我们还在相加和相乘尺度上研究了PM与上述指标对超重/肥胖的相互作用。
单暴露模型显示，较高水平的居住绿地、树木覆盖率以及树木与灌木丛/草地的比例与外周超重/肥胖和中心性肥胖呈负相关。灌木丛、草地的增加以及绿色多样性与外周超重/肥胖几率降低有关。多暴露模型证实了绿色程度与外周超重/肥胖之间的关联。男性、受过教育的参与者以及居住在南部地区和空气环境较清洁地区的老年人从绿地暴露中获得更多益处。单暴露模型和多暴露模型表明，PM增加和绿色程度降低对外周超重/肥胖和中心性肥胖具有拮抗作用。单暴露模型显示了树木覆盖率、树木与草地比例和PM暴露对外周超重/肥胖风险的潜在相互作用。
增加居住绿地和绿色多样性与健康体重状况相关。绿化与超重/肥胖之间的关系各不相同，绿地暴露对超重/肥胖的影响与空气污染有关。
