Abstract:
Background Evidence about the association between air pollution and carotid intima-media thickness (CIMT) is inconsistent, and limited studies have explored the relationship between gaseous pollutants and CIMT. Additionally, personal activity patterns and infiltrated ambient pollution are not comprehensively considered to estimate individual exposure to air pollutants.
Objective To investigate the relationship between long-term time-weighted individual exposure to ambient pollutants fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO) and the progression of CIMT.
Methods This study was performed among 554 participants in the Beijing Health Management Cohort who were free of atherosclerotic lesions on carotid artery at baseline. Daily concentrations of pollutants were predicted at both residential and work addresses based on land-use regression model. With additional consideration of personal indoor and outdoor activity patterns at both addresses and exposure to ambient pollutants from traffic transportation, individual time-weighted concentration was calculated. Indoor exposure was estimated by infiltrated ambient pollutants (based on infiltration factors and land-use regression model). Personal activity patterns included type, time, location, and frequency. Exposure to ambient pollutants from different traffic transportations was estimated by the average outdoor pollutant concentrations at both residential and work addresses combined within filtration factors and time spent on commuting. Multiple linear regression was conducted to assess the association of time-weighted individual pollutant exposure and the central position of CIMT progression. Quantile regression was applied to explore the relationship between time-weighted individual pollutant exposure and the progression of CIMT on different percentiles.
Results The median value of CIMT progression was 369.49 μm·year−1. PM2.5, PM10, SO2, and O3 were associated with CIMT progression in the multiple linear regression model. The largest effect sizes of PM2.5, PM10, and SO2 were obtained for one-year exposure (regression coefficient: 66.910, 64.077, and 191.070, respectively), and two-year exposure for O3 (regression coefficient: 62.197). The results of quantile regression demonstrated different effect sizes for pollutants among different percentiles on CIMT progression. Significant associations between CIMT progression and PM2.5 from P30 to P50, CO from P10 to P40, and PM10 from P30 to P60 were observed. Two-year and three-year exposures to NO2 (P10, P20 and P40) were also associated with CIMT progression. The association between SO2 and the progression of CIMT was proved on all percentiles, and larger effect sizes of one-year and two-year exposures to SO2 (except P90) were demonstrated with increasing percentiles. The upward trend for the coefficients was clearly presented from P50 to P80. Specifically, the coefficient of two-year exposure to SO2 ranged from 136.583 (P50) to 277.330 (P80). No statistically significant association was observed between O3 and CIMT progression on any percentile (P>0.05), and the results were inconsistent with those of the multiple linear regression.
Conclusion Individual time-weighted exposures to PM2.5, PM10, SO2, NO2, and CO have the potential to promote the progression of CIMT, and the adverse effect of ambient pollution on atherosclerotic lesion is identified.