- 期刊
- OpenAccess
Inflammatory Response and PM_(2.5) Exposure of Urban Traffic Conductors
摘要
Human exposure to airborne PM_(2.5) has been linked to an increased risk of respiratory and cardiovascular diseases, possibly via the activation of systemic inflammation. However, the associations between airborne PM_(2.5) and systemic inflammation in humans remain inconclusive. Traffic-related air pollutants (TRAPs) are the major source of PM_(2.5) in urban areas; the adverse health effect of PM_(2.5) from TRAPs is currently a critical issue of public concern. The present cross-sectional study examines the relationship between PM_(2.5) exposure and systemic inflammation in order to consider the health impacts of TRAP PM_(2.5) on urban traffic conductors. All study participants, viz., office-based police officers (the reference) and traffic conductors (the exposure), were requested to carry a personal sampler to determine individual PM_(2.5) exposure. An adenovirus-based NF-κB luciferase reporter assay was used to determine the proinflammatory activity in serum samples collected from the study participants. The blood proinflammatory activity was presented as tumor necrosis factor-α (TNFα) equivalence (TNFα-EQ), which was extrapolated from the sigmoidal semi-logarithmic dose-response curve of the NF-κB reporter assay by TNFα. The levels of both personal PM_(2.5) exposure and blood proinflammatory activity (TNFα-EQ) in the exposure group (traffic conductors) were significantly higher than in the reference group (office-based police officers) (p ＜ 0.05). The present study reveals a positive and significant association between personal PM_(2.5) exposure levels and blood TNFα-EQ levels in a linear regression model of y = 0.511x - 3.062 (y = log TNFα-EQ and x = log PM_(2.5); R = 0.231 and p = 0.047); the results suggest that exposure to TRAP PM_(2.5) significantly contributes to increased systemic inflammation in humans. This research provides clear evidence that long-term occupational exposure to TRAPs causes adverse health impacts, i.e., inflammation, on traffic conductors.
延伸閱讀
- LV, M., LI, Y., CHEN, T., & LI, Y. (2018). Urban Traffic Congestion Index Estimation With Open Ubiquitous Data. Journal of Information Science and Engineering, 34(3), 781-799. https://doi.org/10.6688/JISE.201805_34(3).0013
- 洪郁冠（2015）。A Study on Traffic Safety Parameters under Mixed Traffic Flow〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2015.00956
- Wang, F., Li, M., Fan, J., & Pan, F. (2014). Study on Driver Visual Physiological Characteristics in Urban Traffic. Advances in Mechanical Engineering, 2014(), 176-181. https://doi.org/10.1155/2014/789364
- Li, Z., & Pei, S. (2020). Research on Urban Traffic Control Method Based on Mobile Travel Data. International Core Journal of Engineering, 6(10), 79-84. https://doi.org/10.6919/ICJE.202010_6(10).0014
- Li, Y., Lu, J., Li, H. W., Xiao, H., & Liu, Q. (2015). An Approach to Modeling the Impact of Traffic Incident on Urban Expressway. Discrete Dynamics in Nature and Society, 2015(), 97-104-209. https://doi.org/10.1155/2015/605016