• Ambient air pollution and primary liver cancer incidence in four European cohorts within the ESCAPE project.

      Pedersen, Marie; Andersen, Zorana J; Stafoggia, Massimo; Weinmayr, Gudrun; Galassi, Claudia; Sørensen, Mette; Eriksen, Kirsten T; Tjønneland, Anne; Loft, Steffen; Jaensch, Andrea; et al. (2017)
      Tobacco smoke exposure increases the risk of cancer in the liver, but little is known about the possible risk associated with exposure to ambient air pollution.
    • Associations between lifestyle and air pollution exposure: Potential for confounding in large administrative data cohorts.

      Strak, Maciej; Janssen, Nicole; Beelen, Rob; Schmitz, Oliver; Karssenberg, Derek; Houthuijs, Danny; van den Brink, Carolien; Dijst, Martin; Brunekreef, Bert; Hoek, Gerard (2017)
      Cohorts based on administrative data have size advantages over individual cohorts in investigating air pollution risks, but often lack in-depth information on individual risk factors related to lifestyle. If there is a correlation between lifestyle and air pollution, omitted lifestyle variables may result in biased air pollution risk estimates. Correlations between lifestyle and air pollution can be induced by socio-economic status affecting both lifestyle and air pollution exposure.
    • Comparison of Ultrafine Particle and Black Carbon Concentration Predictions from a Mobile and Short-Term Stationary Land-Use Regression Model.

      Kerckhoffs, Jules; Hoek, Gerard; Messier, Kyle P; Brunekreef, Bert; Meliefste, Kees; Klompmaker, Jochem O; Vermeulen, Roel (2016-12-06)
      Mobile and short-term monitoring campaigns are increasingly used to develop land-use regression (LUR) models for ultrafine particles (UFP) and black carbon (BC). It is not yet established whether LUR models based on mobile or short-term stationary measurements result in comparable models and concentration predictions. The goal of this paper is to compare LUR models based on stationary (30 min) and mobile UFP and BC measurements from a single campaign. An electric car collected both repeated stationary and mobile measurements in Amsterdam and Rotterdam, The Netherlands. A total of 2964 road segments and 161 stationary sites were sampled over two seasons. Our main comparison was based on predicted concentrations of the mobile and stationary monitoring LUR models at 12 682 residential addresses in Amsterdam. Predictor variables in the mobile and stationary LUR model were comparable, resulting in highly correlated predictions at external residential addresses (R2 of 0.89 for UFP and 0.88 for BC). Mobile model predictions were, on average, 1.41 and 1.91 times higher than stationary model predictions for UFP and BC, respectively. LUR models based upon mobile and stationary monitoring predicted highly correlated UFP and BC concentration surfaces, but predicted concentrations based on mobile measurements were systematically higher.
    • Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.

      Burnett, Richard; Chen, Hong; Szyszkowicz, Mieczysław; Fann, Neal; Hubbell, Bryan; Pope, C Arden; Apte, Joshua S; Brauer, Michael; Cohen, Aaron; Weichenthal, Scott; et al. (2018)
      Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.
    • Long-term exposure to ambient air pollution and traffic noise and incident hypertension in seven cohorts of the European study of cohorts for air pollution effects (ESCAPE).

      Fuks, Kateryna B; Weinmayr, Gudrun; Basagaña, Xavier; Gruzieva, Olena; Hampel, Regina; Oftedal, Bente; Sørensen, Mette; Wolf, Kathrin; Aamodt, Geir; Aasvang, Gunn Marit; et al. (2017-04-01)
      We investigated whether traffic-related air pollution and noise are associated with incident hypertension in European cohorts.
    • Nanomaterials Versus Ambient Ultrafine Particles: An Opportunity to Exchange Toxicology Knowledge.

      Stone, Vicki; Miller, Mark R; Clift, Martin J D; Elder, Alison; Mills, Nicholas L; Møller, Peter; Schins, Roel P F; Vogel, Ulla; Kreyling, Wolfgang G; Alstrup Jensen, Keld; et al. (2017)
      A rich body of literature exists that has demonstrated adverse human health effects following exposure to ambient air particulate matter (PM), and there is strong support for an important role of ultrafine (nanosized) particles. At present, relatively few human health or epidemiology data exist for engineered nanomaterials (NMs) despite clear parallels in their physicochemical properties and biological actions inin vitromodels.