Long-term exposure to ambient air pollution and lipid profiles: a longitudinal study in a heavily industrialized region of northern China

Abstract

Dyslipidemia is an important modifiable risk factor for cardiovascular disease, and growing evidence suggests that long-term ambient air pollution exposure may adversely affect lipid metabolism. However, longitudinal evidence from heavily industrialized regions with complex multipollutant exposure remains limited. We conducted a repeated-measures study of 9,040 adults with 19,113 lipid measurements from a health-screening program in Shanxi Province, China, between October 2019 and September 2023. Three-year average exposures to PM 2.5 , PM 10 , O 3 , SO 2 , NO 2 , and CO were estimated using the high-resolution ChinaHighAirPollutants (CHAP) dataset based on geocoded residential addresses. Linear mixed-effects models and generalized linear mixed-effects models were used to evaluate associations with lipid profiles and dyslipidemia, respectively. Restricted cubic spline, stratified, sensitivity, and quantile g-computation-style mixed-effects analyses were further conducted. Higher long-term exposure to PM 2.5 , PM 10 , O 3 , NO 2 , and SO 2 was associated with higher triglyceride (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels and lower high-density lipoprotein cholesterol (HDL-C) levels, whereas CO showed weaker associations. Among pollutants, PM 2.5 showed relatively pronounced associations; each 10 μg/m 3 increase was associated with 1.85, 1.70, and 1.81% increases in TG, TC, and LDL-C, respectively, and a 1.55% decrease in HDL-C. Similar patterns were observed for dyslipidemia. Stratified analyses suggested potential effect modification by sex, age, and BMI for selected pollutant-lipid associations, with the most robust interaction signals observed for age-stratified HDL-C associations after false discovery rate (FDR) correction. The associations remained consistent in sensitivity analyses. Restricted cubic spline analyses suggested nonlinear exposure-response relationships between PM 2.5 and lipid parameters, while the quantile g-computation-style mixed-effects analysis indicated that multipollutant exposure was associated with adverse lipid profiles, with PM 2.5 and O 3 showing relatively large weights in the overall mixed-exposure association. Long-term ambient air pollution exposure was associated with adverse lipid profiles and may be related to higher odds of dyslipidemia among adults in a heavily industrialized region of northern China. These findings suggest that ambient air pollution may be an important environmental factor associated with lipid metabolism and highlight the need to consider long-term multipollutant exposure in cardiometabolic health research and prevention strategies.