Abstract

BACKGROUND AND AIM: __ __Recent studies suggested that certain inflammatory biomarkers and blood lipid indicators may be associated with annual average of ultrafine particle (UFP) exposure. However, associations with repeated peaks of UFP exposure are rarely studied. __We previously proposed a novel metric for assigning UFP peak exposure. We hypothesize that, compared to annual average exposure, cumulative UFP peak exposure over a year may have stronger associations with the aforementioned biomarkers and indicators. METHODS: __ __Blood samples from 452 participants living in the Greater Boston Area were analyzed for three inflammatory biomarkers [high-sensitivity C-reactive protein, interleukin-6 and tumor necrosis factor receptor 2 (TNF-RII)] and four blood lipid indicators [total cholesterol, triglycerides, high-density lipoprotein (HDL) and low-density lipoprotein (LDL)]. __UFP exposure data was hourly averages of particle number concentration (PNC) estimated using a land use regression model based on mobile-monitored ambient UFP concentration, with time-activity adjustment applied. __Both blood sample and UFP exposure data were previously reported in the literature. __Multivariate regression models were used to analyze associations between our peak exposure metric and the outcome biomarkers and indicators. RESULTS:__ __An increase in cumulative UFP peak exposure was significantly associated with a decrease in blood total cholesterol and HDL level. It was also significantly associated with an increase in blood TNF-RII among Non-Hispanic Whites. __The association with total cholesterol level was not found using annual average UFP exposure. __The change of these three outcomes associated with one inter-quartile range’s (IQR) increase in peak exposure was greater than the change associated with one IQR’s increase in annual average exposure. CONCLUSIONS:__ __Associations between UFP exposure and inflammatory biomarkers and blood lipid indicators based on our peak exposure metric were generally similar to associations based on the annual average metric. However, for certain biomarkers and indicators, our peak exposure metric may show stronger associations than the annual average. KEYWORDS: Traffic-related, Particulate matter, Cardiovascular diseases, Exposure assessment, Modeling, Environmental epidemiology

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