Institute for Energy Economics and the Rational Use of Energy, University of Stuttgart, Heßbrühlstraße 49a, 70565 Stuttgart, Germany.
Pierre Louis Institute of Epidemiology and Public Health, Dept of Epidemiology of Allergic and Respiratory Disease, Sorbonne University and INSERM, Paris, France.
Environ Res. 2019 Nov;178:108629. doi: 10.1016/j.envres.2019.108629. Epub 2019 Aug 16.
Numerous epidemiological studies have confirmed the negative influences of air pollutants on human health, where fine particles (PM2.5) and nitrogen dioxide (NO) cause the highest health risks. However, the traditional studies have only involved the ambient concentration for a short to medium time period, which ignores the influence of indoor sources, the individual time-activity pattern, and the fact that the health status is impacted by the long-term accumulated exposure. The aim of this paper is to develop a methodology to simulate the lifelong exposure (rather than outdoor concentration) to PM2.5 and NO for individuals in Europe. This method is realized by developing a probabilistic model that integrates an outdoor air quality model, a model estimating indoor air pollution, an exposure model, and a life course trajectory model for predicting retrospectively the employment status. This approach has been applied to samples of two population studies in the frame of the European Commission FP7-ENVIRONMENT research project HEALS (Health and Environment-wide Associations based on Large Population Surveys), where socioeconomic data of the participants have been collected. Results show that the simulated exposures to both pollutants for the samples are influenced by socio-demographic characteristics, including age, gender, residential location, employment status and smoking habits. Both outdoor concentrations and indoor sources play an important role in the total exposure. Moreover, large variances have been observed among countries and cities. The application of this methodology provides valuable insights for the exposure modelling, as well as important input data for exploring the correlation between exposure and health impacts.
大量的流行病学研究证实了空气污染物对人类健康的负面影响,其中细颗粒物(PM2.5)和二氧化氮(NO)造成的健康风险最高。然而,传统的研究仅涉及短期到中期的环境浓度,忽略了室内来源、个体时间活动模式以及健康状况受到长期累积暴露影响的因素。本文旨在开发一种模拟欧洲个体终生暴露(而非室外浓度)于 PM2.5 和 NO 的方法。该方法通过开发一个概率模型来实现,该模型集成了室外空气质量模型、室内空气污染估算模型、暴露模型和用于回溯预测就业状况的生活轨迹模型。该方法已应用于欧盟委员会 FP7-ENVIRONMENT 研究项目 HEALS(基于大型人群调查的健康和环境广泛关联)框架内的两项人群研究的样本中,其中收集了参与者的社会经济数据。结果表明,模拟样本中这两种污染物的暴露量受社会人口统计学特征的影响,包括年龄、性别、居住地点、就业状况和吸烟习惯。室外浓度和室内来源在总暴露中都起着重要作用。此外,还观察到各国和各城市之间存在较大差异。该方法的应用为暴露建模提供了有价值的见解,并为探索暴露与健康影响之间的相关性提供了重要的输入数据。