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Sökning: WFRF:(Molter A)

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  • Molter, A, et al. (författare)
  • A multicentre study of air pollution exposure and childhood asthma prevalence: the ESCAPE project
  • 2015
  • Ingår i: The European respiratory journal. - : European Respiratory Society (ERS). - 1399-3003 .- 0903-1936. ; 45:3, s. 610-624
  • Tidskriftsartikel (refereegranskat)abstract
    • The aim of this study was to determine the effect of six traffic-related air pollution metrics (nitrogen dioxide, nitrogen oxides, particulate matter with an aerodynamic diameter <10 μm (PM10), PM2.5, coarse particulate matter and PM2.5 absorbance) on childhood asthma and wheeze prevalence in five European birth cohorts: MAAS (England, UK), BAMSE (Sweden), PIAMA (the Netherlands), GINI and LISA (both Germany, divided into north and south areas).Land-use regression models were developed for each study area and used to estimate outdoor air pollution exposure at the home address of each child. Information on asthma and current wheeze prevalence at the ages of 4–5 and 8–10 years was collected using validated questionnaires. Multiple logistic regression was used to analyse the association between pollutant exposure and asthma within each cohort. Random-effects meta-analyses were used to combine effect estimates from individual cohorts.The meta-analyses showed no significant association between asthma prevalence and air pollution exposure (e.g. adjusted OR (95%CI) for asthma at age 8–10 years and exposure at the birth address (n=10377): 1.10 (0.81–1.49) per 10 μg·m-3 nitrogen dioxide; 0.88 (0.63–1.24) per 10 μg·m-3 PM10; 1.23 (0.78–1.95) per 5 μg·m-3 PM2.5). This result was consistently found in initial crude models, adjusted models and further sensitivity analyses.This study found no significant association between air pollution exposure and childhood asthma prevalence in five European birth cohorts.
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  • Sawicki, J., et al. (författare)
  • Perspectives on adaptive dynamical systems
  • 2023
  • Ingår i: Chaos. - 1054-1500 .- 1089-7682. ; 33:7
  • Tidskriftsartikel (refereegranskat)abstract
    • Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches.
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