Association of long-term exposure to local industry- and traffic-specific particulate matter with arterial blood pressure and incident hypertension.
Association of long-term exposure to local industry- and traffic-specific particulate matter with arterial blood pressure and incident hypertension.
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DOI：
10.1016/j.ijheh.2016.05.008
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发表时间：
2016-08-01
影响因子：
6
通讯作者：
Hoffmann, Barbara
中科院分区：
文献类型：
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作者：
Fuks, Kateryna B;Weinmayr, Gudrun;Hoffmann, Barbara
背景：长期暴露于细颗粒物（PM2.5）可能导致血压升高。工业和交通特定的PM2.5的作用尚不清楚。目的：在以人群为基础的Heinz Nixdorf回忆队列研究中，我们调查了长期居住源特异性PM2.5暴露与动脉血压和高血压事件的关系。方法：我们将高血压定义为收缩压≥140mmHg，或舒张压≥90mmHg，或目前使用降压药物。采用分辨率为1km(2)的扩散和化学输运模型（EURAD-CTM）模拟了所有当地污染源（PM2.5 all）、当地工业（PM2.5 ind）和交通（PM2.5 tra）的PM2.5长期浓度。我们分别使用线性和逻辑回归对基线时的血压和高血压进行了横断面分析，并使用稳健方差估计的泊松回归对5年随访时的高血压事件进行了纵向分析。我们根据年龄、性别、身体质量指数、生活方式、教育程度和主要道路距离进行了调整。计算每1mug/m(3)暴露浓度下血压（mmHg）、优势比（OR）和高血压相对危险度（RR）的变化。结果：PM2.5ALL与PM2.5IND高度相关（Spearman’s rho=0.92），与PM2.5TRA中度相关（rho=0.42）。在4539名参与者的校正横断面分析中，我们发现PM2.5ALL与收缩压（0.42 [95%-CI: 0.03, 0.80]）和舒张压（0.25[0.04,0.46]）呈正相关。PM2.5IND（收缩压：0.55[-0.05,1.14]；舒张压：0.35[0.03,0.67]）和PM2.5TRA（收缩压：0.88[-1.55,3.31]；舒张压：0.41[-0.91,1.73]）的估计值较高，但精度较低。我们发现PM2.5TRA与患病率（OR 1.41[1.10, 1.80]）和高血压发病率（RR 1.38[1.03, 1.85]）呈正相关，调整后呈减弱趋势（OR 1.19 [0.90, 1.58], RR 1.28[0.94, 1.72]）。我们发现PM2.5ALL和PM2.5IND与高血压没有关联。结论：长期暴露于全源PM2.5和行业特异性PM2.5与BP呈正相关。我们无法将行业特定PM2.5的影响与全源PM2.5的影响分开。根据具体交通状况估算的PM2.5总体较高，但尚无定论。
BACKGROUND: Long-term exposure to fine particulate matter (PM2.5) may lead to increased blood pressure (BP). The role of industry- and traffic-specific PM2.5 remains unclear.OBJECTIVE: We investigated the associations of residential long-term source-specific PM2.5 exposure with arterial BP and incident hypertension in the population-based Heinz Nixdorf Recall cohort study.METHODS: We defined hypertension as systolic BP≥140mmHg, or diastolic BP≥90mmHg, or current use of BP lowering medication. Long-term concentrations of PM2.5 from all local sources (PM2.5ALL), local industry (PM2.5IND) and traffic (PM2.5TRA) were modeled with a dispersion and chemistry transport model (EURAD-CTM) with a 1km(2) resolution. We performed a cross-sectional analysis with BP and prevalent hypertension at baseline, using linear and logistic regression, respectively, and a longitudinal analysis with incident hypertension at 5-year follow-up, using Poisson regression with robust variance estimation. We adjusted for age, sex, body mass index, lifestyle, education, and major road proximity. Change in BP (mmHg), odds ratio (OR) and relative risk (RR) for hypertension were calculated per 1mug/m(3) of exposure concentration.RESULTS: PM2.5ALL was highly correlated with PM2.5IND (Spearman's rho=0.92) and moderately with PM2.5TRA (rho=0.42). In adjusted cross-sectional analysis with 4539 participants, we found positive associations of PM2.5ALL with systolic (0.42 [95%-CI: 0.03, 0.80]) and diastolic (0.25 [0.04, 0.46]) BP. Higher, but less precise estimates were found for PM2.5IND (systolic: 0.55 [-0.05, 1.14]; diastolic: 0.35 [0.03, 0.67]) and PM2.5TRA (systolic: 0.88 [-1.55, 3.31]; diastolic: 0.41 [-0.91, 1.73]). We found crude positive association of PM2.5TRA with prevalence (OR 1.41 [1.10, 1.80]) and incidence of hypertension (RR 1.38 [1.03, 1.85]), attenuating after adjustment (OR 1.19 [0.90, 1.58] and RR 1.28 [0.94, 1.72]). We found no association of PM2.5ALL and PM2.5IND with hypertension.CONCLUSIONS: Long-term exposures to all-source and industry-specific PM2.5 were positively related to BP. We could not separate the effects of industry-specific PM2.5 from all-source PM2.5. Estimates with traffic-specific PM2.5 were generally higher but inconclusive.