Institute for Medical Information Processing, Biometry and Epidemiology - IBE, LMU Munich, Munich, Germany; Pettenkofer School of Public Health, Munich, Germany; Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany.
Institute of Epidemiology, Helmholtz Zentrum München GmbH - German Research Center for Environmental Health, Neuherberg, Germany.
Environ Int. 2021 Feb;147:106364. doi: 10.1016/j.envint.2020.106364. Epub 2021 Jan 6.
A growing number of epidemiological studies show associations between environmental factors and impaired cardiometabolic health. However, evidence is scarce concerning these risk factors and their impact on metabolic syndrome (MetS). This analysis aims to investigate associations between long-term exposure to air pollution, road traffic noise, residential greenness, and MetS.
We used data of the first (F4, 2006-2008) and second (FF4, 2013-2014) follow-up of the population-based KORA S4 survey in the region of Augsburg, Germany, to investigate associations between exposures and MetS prevalence at F4 (N = 2883) and MetS incidence at FF4 (N = 1192; average follow-up: 6.5 years). Residential long-term exposures to air pollution - including particulate matter (PM) with a diameter < 10 µm (PM), PM < 2.5 µm (PM), PM between 2.5 and 10 µm (PM), absorbance of PM (PM2.5), particle number concentration (PNC), nitrogen dioxide (NO), ozone (O) - and road traffic noise were modeled by land-use regression models and noise maps. For greenness, the Normalized Difference Vegetation Index (NDVI) was obtained. We estimated Odds Ratios (OR) for single and multi-exposure models using logistic regression and generalized estimating equations adjusted for confounders. Joint Odds Ratios were calculated based on the Cumulative Risk Index. Effect modifiers were examined with interaction terms.
We found positive associations between prevalent MetS and interquartile range (IQR) increases in PM (OR: 1.15; 95% confidence interval [95% CI]: 1.02, 1.29), PM (OR: 1.14; 95% CI: 1.02, 1.28), PM (OR: 1.14; 95% CI: 1.02, 1.27), and PMabs (OR: 1.17; 95% CI: 1.03, 1.32). Results further showed negative, but non-significant associations between exposure to greenness and prevalent and incident MetS. No effects were seen for exposure to road traffic noise. Joint Odds Ratios from multi-exposure models were higher than ORs from models with only one exposure.
越来越多的流行病学研究表明,环境因素与心脏代谢健康受损之间存在关联。然而,关于这些危险因素及其对代谢综合征(MetS)的影响的证据还很缺乏。本分析旨在研究长期暴露于空气污染、道路交通噪声、居住绿化与 MetS 之间的关系。
我们使用德国奥格斯堡地区基于人群的 KORA S4 调查的第一(F4,2006-2008 年)和第二(FF4,2013-2014 年)随访的数据,研究了 F4 时(N=2883)的暴露与 MetS 患病率和 FF4 时(N=1192;平均随访时间:6.5 年)的 MetS 发生率之间的关系。采用基于土地利用的回归模型和噪声图对长期居住环境中的空气污染(包括直径<10 µm 的颗粒物(PM)、<2.5 µm 的颗粒物(PM)、2.5-10 µm 之间的颗粒物(PM)、PM 的吸光度(PM2.5)、颗粒物数浓度(PNC)、二氧化氮(NO)、臭氧(O))和道路交通噪声进行建模。对于绿化程度,采用归一化植被指数(NDVI)来表示。我们使用逻辑回归和广义估计方程,在调整了混杂因素后,对单一和多暴露模型的比值比(OR)进行了估计。基于累积风险指数计算联合比值比。通过交互项检验了效应修饰因子。
我们发现,与 MetS 患病率相关的指标中,PM(OR:1.15;95%置信区间[95%CI]:1.02,1.29)、PM(OR:1.14;95%CI:1.02,1.28)、PM(OR:1.14;95%CI:1.02,1.27)和 PMabs(OR:1.17;95%CI:1.03,1.32)的 IQR 每增加一个单位,患病率就会增加。进一步的结果显示,与绿化相关的指标与现患和新发 MetS 呈负相关,但无统计学意义。道路交通噪声的暴露没有影响。多暴露模型的联合比值比高于仅一个暴露的模型的比值比。