Association of systemic inflammation and coagulation biomarkers with source-specific PM2.5 mass concentrations among elderly and young subjects in central Tehran.

In this study, we investigated the association between short-term exposure to different sources of fine particulate matter (PM2.5) and biomarkers of coagulation and inflammation in two different panels of elderly and healthy young individuals in central Tehran. Five biomarkers, including white blood cells (WBC), high sensitive C-reactive protein (hsCRP), tumor necrosis factor-soluble receptor-II (sTNF-RII), interleukin-6 (IL-6), and von Willebrand factor (vWF) were analyzed in the blood samples drawn every 8 weeks from the subjects between May 2012 and May 2013. The studied populations consisted of 44 elderly individuals at a retirement home as well as 40 young adults residing at a school dormitory. PMF-resolved source-specific PM2.5 mass concentrations and biomarker levels were used as the input to the linear mixed-effects regression model to evaluate the impact of exposure to previously identified PM sources at retirement home and school dormitory in two time lag configurations: lag 1-3 (1-3 days before the blood sampling), and lag 4-6 (4-6 days before the blood sampling). Our analysis of the elderly revealed positive associations of all biomarkers (except hsCRP) with particles of secondary origin in both time lags, further corroborating the toxicity of secondary aerosols formed by photochemical processing in central Tehran. Moreover, industrial emissions, and road dust particles were positively associated with WBC, sTNF-RII and IL-6 among seniors, while vehicular emissions exhibited positive associations with all biomarkers in either first- or second-time lag. In contrast, most of the PM2.5 sources showed insignificant associations with biomarkers of inflammation in the panel of healthy young subjects. Therefore, findings from this study indicated that various PM2.5 sources increase the levels of inflammation and coagulation biomarkers, although the strength and significance of these associations vary depending on the type of PM sources, demographic characteristics, and differ across the different time lags.