期刊名称：The International Journal of Occupational and Environmental Medicine
印刷版ISSN：2008-6520
电子版ISSN：2008-6814
出版年度：2017
卷号：8
期号：3
页码：131-42
DOI：10.15171/ijoem.2017.1073
语种：English
出版社：National Iranian Oil Company (NIOC) Health Organization
摘要：Background: The public health burden of hypertension is high, but its relationship with long-term residential air pollution, road traffic, and greenness remains unclear.Objective: To investigate associations between residential air pollution, traffic, greenness, and hypertension among mothers.Methods: Information on doctor-diagnosed maternal hypertension was collected at the 15-year follow-up of two large population-based multicenter German birth cohorts—GINIplus and LISAplus (n=3063). Residential air pollution was modelled by land use regression models within the ESCAPE and universal kriging within the APMoSPHERE projects. Road traffic was defined as traffic load on major roads within a 100-m buffer around residences. Vegetation level (ie, greenness) was defined as the mean Normalized Difference Vegetation Index in a 500-m buffer around residences and was assessed from Landsat 5 TM satellite images. All the exposure variables were averaged over three residential addresses during the last 10 years and categorized into tertiles or dichotomized. The individual associations between each of the exposure variables and hypertension were assessed using logistic regression analysis.Results: No significant and consistent associations across different levels of adjustment were observed between the exposures of interest and hypertension. The only significant estimate was found with coarse particulate matter concentrations (OR 1.66, 95% CI 1.01 to 2.74; 3rd vs 1st tertile) among mothers residing in the Wesel area. No significant associations were observed with traffic load or greenness.Conclusion: This study does not provide evidence on detrimental effects of air pollution and road traffic or beneficial effects of greenness on hypertension among German adults.
关键词：Hypertension; Air pollution; Cohort studies; Satellite imagery; Geographic information systems; Remote sensing technology; Risk factors
