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 (PM_2.5), 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. PM_2.5, PM₁₀, SO₂, and O₃ were associated with CIMT progression in the multiple linear regression model. The largest effect sizes of PM_2.5, 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 PM_2.5 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 PM_2.5, 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.

Background Few studies have investigated the association between air pollution and arterial stiffness in Chinese population, and the findings are inconsistent. The problem of multicollinearity exists when modeling multiple air pollutants simultaneously. Objective To investigate potential association between air quality index (AQI) and population brachial-ankle pulse wave velocity (baPWV) in Beijing. Methods This study retrieved medical examination data of 2971 participants from the Beijing Health Management Cohort, who were under 60 years old and not yet retired, from January 1, 2015 to December 31, 2019. The most recent medical examination data available were utilized for this analysis. AQI data from 35 air pollution monitoring sites in Beijing and meteorological data (including atmospheric pressure, air temperature, wind speed, and relative humidity) from 16 meteorological monitoring stations from January 1, 2014 to December 31, 2019 were collected. An average AQI exposure level for 365 d before the date of physical examination for each participant was computed using inverse distance weighting. Multiple linear regression analysis was employed to investigate the relationship between AQI and baPWV in Beijing, after adjusting for confounding variables including age, gender, body mass index, mean arterial pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, fasting blood glucose, atmospheric pressure, temperature, wind speed, relative humidity, medication history of diabetes, medication history of hypertension, cardiovascular disease, education, smoking status, drinking status, and physical activity intensity. Subgroup analysis was performed by age, sex, presence of diabetes, and presence of hypertension. Results AQI demonstrated an overall decreasing trend during the study period and was lower in the northern regions and higher in the southern regions of Beijing. After adjusting the confounding variables, each 10 unit increase in AQI was associated with 6.18 (95%CI: 1.25, 11.10) cm·s⁻¹ increase in baPWV in all participants, 8.05 (95%CI: 2.32, 13.79) cm·s⁻¹ increase in the participants <50 years, 15.82 (95%CI: 8.33, 23.31) cm·s⁻¹ increase in the female group, 10.10 (95%CI: 4.66, 15.55) cm·s⁻¹ increase in the participants without diabetes, and 9.41 (95%CI: 4.21, 14.62) cm·s⁻¹ increase in the participants without hypertension. However, there was no statistically significant association observed between AQI and baPWV in the age group ≥50 years, the male group, the diabetic group, and the hypertensive group (P>0.05). Conclusion An increase in long-term AQI levels is associated with an elevation in the degree of arterial stiffness. Individuals under 50 years old, females, without hypertension or diabetes are susceptible populations to arterial stiffness when being exposed to air pollution. Improving air quality may contribute to prevent arterial stiffness.