| Summary: | 碩士 === 國防醫學院 === 公共衛生學研究所 === 106 === Background
Polycyclic aromatic hydrocarbons (PAHs) and metals may be adsorbed on the surface of fine particulate matter (PM2.5), of which may cause adverse health effects to humans. But limited information exists regarding the co-exposure of metals and PAHs on DNA damages. Furthermore, limited references explored the relationship between different exposure assessment methods and oxidative damage biomarkers.
Aim
1. To explore the relation between PM2.5 exposure assessments (Personal sampling, monitor station, Inverse Distance Weighting model [IDW], Land Use Regression model [LUR]) and oxidative stress.
2. To explore the relation between PM2.5, metal, 1-OHP and oxidative stress (HEL, 8-OHdG, N7-methylguanine [N7-MeG]).
3. To explore the interaction between PM2.5, metal, 1-OHP and oxidative stress.
Method
This study was conducted in a longitudinal design. We recruited 82 healthy students from 2 areas. All collection procedures were repeated twice after a two-month follow-up period. We used personal samplers to collect 24 hours PM2.5 samples. Hourly levels of ambient PM2.5, daily temperature and relative humidity were measured from monitoring stations. Blood and urine samples were collected the next morning.
Results
In cross-sectional analysis, a significant correlation between PM2.5 exposure assessments (personal sampling, monitor station, IDW, LUR). Urinary 1-OHP was positively related to HEL and blood V was related to N7-MeG. In longitudinal analyses, all the PM2.5 exposure assessments were associated with HEL and N7-MeG. Urinary 1-OHP was positively associated with oxidative damage biomarkers (HEL, 8-OHdG, N7-MeG). Metals in filter (V, Mn, Pb) were positively associated with oxidative stress (HEL). Metals in filter (V, Mn, Ni, Zn) were positively associated with oxidative stress (N7-MeG). Urinary metals (V, Zn, As) were positively associated with oxidative stress (HEL, 8-OHdG, N7-MeG) simultaneously. No synergistic effect was found between urinary metals and urinary 1-OHP on any oxidative damage biomarkers.
Conclusion
Data from air monitoring stations and model estimation (IDW, LUR model) are good exposure assessment methods for assessing PM2.5 exposure. Metal and PAHs exposures may increase oxidative stress independently, but no additive interaction effect from co-exposure of metal and PAHs.
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