@article{01GNVGPNAZNTA1X2TYYBKHAK5D,
  abstract     = {{The effects of exposure to black carbon (BC) on various diseases remains unclear, one reason being potential exposure misclassification following modelling of ambient air pollution levels. Urinary BC particles may be a more precise measure to analyze the health effects of BC. We aimed to assess the risk of prediabetes and metabolic syndrome (MetS) in relation to urinary BC particles and ambient BC and to compare their associations in 5453 children from IDEFICS/I. Family cohort. We determined the amount of BC particles in urine using label-free white-light generation under femtosecond pulsed laser illumination. We assessed annual exposure to ambient air pollutants (BC, PM2.5 and NO2) at the place of residence using land use regression models for Europe, and we calculated the residential distance to major roads (<= 250 m vs. more). We analyzed the cross-sectional relationships between urinary BC and air pollutants (BC, PM2.5 and NO2) and distance to roads, and the associations of all these variables to the risk of prediabetes and MetS, using logistic and linear regression models. Though we did not observe associations between urinary and ambient BC in overall analysis, we observed a positive association between urinary and ambient BC levels in boys and in children living <= 250 m to a major road compared to those living >250 m away from a major road. We observed a positive association between log-transformed urinary BC particles and MetS (ORper unit increase = 1.72, 95% CI = 1.21; 2.45). An association between ambient BC and MetS was only observed in children living closer to a major road. Our findings suggest that exposure to BC (ambient and biomarker) may contribute to the risk of MetS in children. By measuring the internal dose, the BC particles in urine may have additionally captured non-residential sources and reduced exposure misclassification. Larger studies, with longitudinal design including measurement of urinary BC at multiple time-points are warranted to confirm our findings.}},
  articleno    = {{120773}},
  author       = {{Nagrani, Rajini and Marron, Manuela and Bongaerts, Eva and Nawrot, Tim S. and Ameloot, Marcel and de Hoogh, Kees and Vienneau, Danielle and Lequy, Emeline and Jacquemin, Bénédicte and Guenther, Kathrin and De Ruyter, Thaïs and Mehlig, Kirsten and Molnár, Dénes and Moreno, Luis A. and Russo, Paola and Veidebaum, Toomas and Ahrens, Wolfgang and Buck, Christoph}},
  issn         = {{0269-7491}},
  journal      = {{ENVIRONMENTAL POLLUTION}},
  keywords     = {{Health, Toxicology and Mutagenesis,Pollution,Toxicology,General Medicine,Urine biomarker,Metabolic syndrome,Prediabetes,Black carbon,Air pollution,Children cohort}},
  language     = {{eng}},
  pages        = {{12}},
  publisher    = {{Elsevier BV}},
  title        = {{Association of urinary and ambient black carbon, and other ambient air pollutants with risk of prediabetes and metabolic syndrome in children and adolescents}},
  url          = {{http://doi.org/10.1016/j.envpol.2022.120773}},
  volume       = {{317}},
  year         = {{2023}},
}

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