Brown Jack R G, Baptiste Paris J, Hajmohammadi Hajar, Nadarajah Ramesh, Gale Chris P, Wu Jianhua
Centre for Primary Care, Wolfson Institute of Population Health, Queen Mary University of London, London, UK.
Leeds Institute of Data Analytics, University of Leeds, Leeds, UK.
Eur J Prev Cardiol. 2025 Mar 19. doi: 10.1093/eurjpc/zwaf165.
We aimed to study the association of five key neighbourhood exposures in large cohort studies and risk of incident cardiovascular disease (CVD).
We conducted a systematic search of MEDLINE, The Cochrane Library, Web of Science, and Embase from database inception to 20th October 2024. Included studies reported both incident (first-time) CVD diagnosis and neighbourhood exposures across five domains: retail environment; health services; physical environment; pollution; and neighbourhood deprivation. A random-effects meta-analysis was performed to estimate pooled risk of CVD across domains.
Of 39 studies included in the systematic review, 28 qualified for meta-analysis representing over 41 million people. The most frequently examined exposures were air pollution (n=17), followed by noise pollution (n=9), socioeconomic (n=6), green and blue spaces (n=3), and health and retail environments (n=4). Higher concentrations of particulate matter 2.5 (PM2.5; HR: 1.16 [95% CI: 1.09-1.24] per 10 µg/m³ increase), higher nitrogen dioxide (NO2; HR: 1.05 [95% CI: 1.02-1.07] per 10 ppb increase), road traffic noise (RR: 1.03 [95% CI: 1.02-1.05] per 10dB increase), and high neighbourhood-level deprivation (RR: 1.24 [95% CI: 1.17-1.31] vs. low) were each associated with increased risk of incident CVD development.
Our findings indicate a modest yet significant increase in CVD risk associated with elevated levels of air pollution, road noise and neighbourhood deprivation, emphasising these exposures as consequential targets for policy intervention.
我们旨在通过大型队列研究，探讨五个关键社区暴露因素与心血管疾病（CVD）发病风险之间的关联。
我们对MEDLINE、Cochrane图书馆、科学网和Embase进行了系统检索，检索时间跨度从数据库建立至2024年10月20日。纳入的研究需同时报告心血管疾病（首次）诊断情况以及五个领域的社区暴露因素：零售环境、医疗服务、物理环境、污染和社区贫困状况。采用随机效应荟萃分析来估计各领域心血管疾病的综合发病风险。
在系统评价纳入的39项研究中，28项符合荟萃分析标准，涉及超过4100万人。研究最多的暴露因素是空气污染（n = 17），其次是噪音污染（n = 9）、社会经济因素（n = 6）、绿地和蓝地（n = 3）以及医疗和零售环境（n = 4）。细颗粒物2.5（PM2.5）浓度每增加10μg/m³，心血管疾病发病风险升高（HR：1.16 [95% CI：1.09 - 1.24]）；二氧化氮（NO2）浓度每增加10 ppb，心血管疾病发病风险升高（HR：1.05 [95% CI：1.02 - 1.07]）；道路交通噪音每增加10 dB，心血管疾病发病风险升高（RR：1.03 [95% CI：1.02 - 1.05]）；社区贫困程度高者相比贫困程度低者，心血管疾病发病风险升高（RR：1.24 [95% CI：1.17 - 1.31]）。
我们的研究结果表明，空气污染、道路噪音和社区贫困程度升高与心血管疾病风险适度但显著增加相关，强调这些暴露因素是政策干预的重要目标。
