Associations of PM2.5 and its constituents with blood lipids: A national longitudinal study in China

• PM2.5 constituents are linked to adverse lipid changes in a longitudinal study. • SIA components show the strongest associations with adverse blood lipid levels. • PM 2.5 constituents exhibit non-linear and non-threshold exposure-response curves. • Males, the elderly, and those with abnormal BMI are more susceptible to exposure. The association between fine particulate matter (PM 2.5 ) chemical constituents and blood lipid levels remains unclear. This longitudinal study, leveraging data from a comprehensive national survey across 31 provinces in mainland China, aimed to assess the associations between exposure to PM 2.5 constituents and blood lipid metabolism. Utilizing data from the China National Stroke Screening Survey (CNSSS), we included 292,754 participants accounting for 683,759 visits recorded between 2013 and 2019. To investigate the longitudinal relationship between PM 2.5 , its five constituents (ammonium, sulfate, nitrate, black carbon (BC), and organic matter (OM)), and four blood lipid indicators (low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDLC), triglyceride (TG), and total cholesterol (TC)), we employed linear fixed-effects panel regression models. Each interquartile range (IQR) increase in PM 2.5 (lag 0-3 months) was associated with significant increases in LDLC (3.44%, 95% CI: 3.07–3.80) and TC (2.99%, 95% CI: 2.70–3.28), and a decrease in HDLC (-0.89%, 95% CI: -1.17 to -0.62). For constituents, ammonium and nitrate showed the strongest associations with LDLC (4.66% and 4.76%, respectively) and TC (3.72% and 3.60%, respectively). TG levels were positively associated with secondary inorganic aerosols, most notably sulfate (2.91%, 95% CI: 2.50–3.33). Significant negative correlations with HDLC were observed for BC (-0.46%, 95% CI: -0.72 to -0.19) and sulfate (-0.71%, 95% CI: -1.04 to -0.38). The exposure-response relationships between the constituents and blood lipid indicators were predominantly nonlinear, characterized by a plateau at higher concentration levels. Our results indicate that exposure to PM 2.5 and its constituents, especially inorganic aerosol components, was strongly associated with adverse blood lipid levels. The findings of our study provide critical insights into policy development aimed at enhancing the management and control of PM 2.5 pollution.

Authors

Institutions

Publication Details

Journal
Hygiene and Environmental Health Advances
Published
2026-05-01
DOI
https://doi.org/10.1016/j.heha.2026.100183
Primary Topic
Air Quality and Health Impacts
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Associations of PM2.5 and its constituents with blood lipids: A national longitudinal study in China

Tianjia Guan, Hanchao Cheng, T J Wang, Ying Liu et al.
Hygiene and Environmental Health Advances
Air Quality and Health Impacts
article

Associations of PM2.5 and its constituents with blood lipids: A national longitudinal study in China

Tianjia Guan, Hanchao Cheng, T J Wang, Ying Liu, Yuxing Wang, Jian Guo, Zhaoyang Pan, Hailu Zhu, Xueyan Han, Qi Wang
article en

Abstract

• PM2.5 constituents are linked to adverse lipid changes in a longitudinal study. • SIA components show the strongest associations with adverse blood lipid levels. • PM 2.5 constituents exhibit non-linear and non-threshold exposure-response curves. • Males, the elderly, and those with abnormal BMI are more susceptible to exposure. The association between fine particulate matter (PM 2.5 ) chemical constituents and blood lipid levels remains unclear. This longitudinal study, leveraging data from a comprehensive national survey across 31 provinces in mainland China, aimed to assess the associations between exposure to PM 2.5 constituents and blood lipid metabolism. Utilizing data from the China National Stroke Screening Survey (CNSSS), we included 292,754 participants accounting for 683,759 visits recorded between 2013 and 2019. To investigate the longitudinal relationship between PM 2.5 , its five constituents (ammonium, sulfate, nitrate, black carbon (BC), and organic matter (OM)), and four blood lipid indicators (low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDLC), triglyceride (TG), and total cholesterol (TC)), we employed linear fixed-effects panel regression models. Each interquartile range (IQR) increase in PM 2.5 (lag 0-3 months) was associated with significant increases in LDLC (3.44%, 95% CI: 3.07–3.80) and TC (2.99%, 95% CI: 2.70–3.28), and a decrease in HDLC (-0.89%, 95% CI: -1.17 to -0.62). For constituents, ammonium and nitrate showed the strongest associations with LDLC (4.66% and 4.76%, respectively) and TC (3.72% and 3.60%, respectively). TG levels were positively associated with secondary inorganic aerosols, most notably sulfate (2.91%, 95% CI: 2.50–3.33). Significant negative correlations with HDLC were observed for BC (-0.46%, 95% CI: -0.72 to -0.19) and sulfate (-0.71%, 95% CI: -1.04 to -0.38). The exposure-response relationships between the constituents and blood lipid indicators were predominantly nonlinear, characterized by a plateau at higher concentration levels. Our results indicate that exposure to PM 2.5 and its constituents, especially inorganic aerosol components, was strongly associated with adverse blood lipid levels. The findings of our study provide critical insights into policy development aimed at enhancing the management and control of PM 2.5 pollution.

Hygiene and Environmental Health Advances
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Peking Union Medical College Hospital (CN)
Good health and well-being
Openalex Percentile: Top 7%
Air Quality and Health Impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.