Song Jian, Du Peng, Yi Weizhuo, Wei Jing, Fang Jianlong, Pan Rubing, Zhao Feng, Zhang Yi, Xu Zhiwei, Sun Qinghua, Liu Yingchun, Chen Chen, Cheng Jian, Lu Yifu, Li Tiantian, Su Hong, Shi Xiaoming
Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China.
Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, No. 81 Meishan Road, Shushan District, Hefei, Anhui 230031, China.
Environ Sci Technol. 2022 Jun 21;56(12):8395-8405. doi: 10.1021/acs.est.1c08327. Epub 2022 Jun 2.
Existing studies mostly explored the association between urban environmental exposures and blood pressure (BP) in isolation, ignoring correlations across exposures. This study aimed to systematically evaluate the impact of a wide range of urban exposures on BP using an exposome-wide approach. A multicenter cross-sectional study was conducted in ten cities of China. For each enrolled participant, we estimated their urban exposures, including air pollution, built environment, surrounding natural space, and road traffic indicator. On the whole, this study comprised three statistical analysis steps, that is, single exposure analysis, multiple exposure analysis and a cluster analysis. We also used deletion-substitution-addition algorithm to conduct variable selection. After considering multiple exposures, for hypertension risk, most significant associations in single exposure model disappeared, with only neighborhood walkability remaining negatively statistically significant. Besides, it was observed that SBP (systolic BP) raised gradually with the increase in PM, but such rising pattern slowed down when PM concentration reached a relatively high level. For surrounding natural spaces, significant protective associations between green and blue spaces with BP were found. This study also found that high population density and public transport accessibility have beneficially significant association with BP. Additionally, with the increase in the distance to the nearest major road, DBP (diastolic BP) decreased rapidly. When the distance was beyond around 200 m, however, there was no obvious change to DBP anymore. By cluster analysis, six clusters of urban exposures were identified. These findings reinforce the importance of improving urban design, which help promote healthy urban environments to optimize human BP health.
现有研究大多孤立地探讨城市环境暴露与血压(BP)之间的关联,而忽略了暴露之间的相关性。本研究旨在采用全暴露组方法系统评估多种城市暴露因素对血压的影响。在中国的十个城市开展了一项多中心横断面研究。对于每一位纳入的参与者,我们估算了他们的城市暴露因素,包括空气污染、建成环境、周边自然空间和道路交通指标。总体而言,本研究包括三个统计分析步骤,即单暴露分析、多暴露分析和聚类分析。我们还使用删除-替代-添加算法进行变量选择。在考虑多种暴露因素后,对于高血压风险,单暴露模型中大多数显著关联消失,仅邻里可达性仍具有负向统计学显著性。此外,观察到收缩压(SBP)随着颗粒物(PM)增加而逐渐升高,但当PM浓度达到相对较高水平时,这种上升趋势减缓。对于周边自然空间,发现绿地和蓝空间与血压之间存在显著的保护关联。本研究还发现,高人口密度和公共交通可达性与血压存在有益的显著关联。此外,随着与最近主要道路距离的增加,舒张压(DBP)迅速下降。然而,当距离超过约200米时,DBP不再有明显变化。通过聚类分析,识别出六类城市暴露因素。这些发现强化了改善城市设计的重要性,这有助于促进健康的城市环境以优化人类血压健康。