Association of black carbon particles and risk of pre-diabetes


The objectives of the proposal are to measure black carbon particles in urine and assess ist association with insulin resistance within the well described youth cohort of the IDEFICS/I.Family study. The proposal will assess the association using both cross-sectional and longitudinal analyses. To achieve the objectives comprehensively, the chronic exposure to combustion related air pollution will be assessed by the newly identified novel biomarker of internal dose (urinary carbon load) which will be utilised for the first time in disease prediction model. This technique will use label-free white-light generation detection femtosecond pulsed laser illumination to determine the amount of black carbon particles in urine. For the information on disease outcome, the study will exploit laboratory data on insulin resistance quantified by homeostasis model assessment-insulin resistance (HOMA‐IR) from two surveys. The proposal will also include baseline and follow-up data from questionnaire data for information on covariates. For Statistical analysis, Generalised additive models will be used to assess the linearity of associations between insulin resistance and urinary black carbon. Subsequently multiple linear regression models will be used to assess the independent association between urinary carbon load and insulin resistance. Linear mixed effects models will be fitted to estimate the longitudinal relationship between HOMA-IR and urinary black carbon.

Funding period

Begin:   July 2019
End:   February 2022


  • BIPS funding (Institute's intramural fund)


Dr. Rajini Nagrani