Evidence map›Paper›PMID 41975355›Full record

ArticleBMC public health2026

Spatial heterogeneity and population susceptibility in the association between ambient nitrogen dioxide exposure and lipid profiles: a nationwide longitudinal cohort.

Jian Guo, Zhenzhen Rao, Wei Sun, Hailu Zhu, Zhaoyang Pan, Qi Wang, Yicong Wang, Yuanli Liu, Tianjia Guan

Abstract read
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jian Guo *State Key Laboratory for Complex, Severe, and Rare Diseases, Beijing, 100730, China.
Zhenzhen Rao *Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan, 410078, China.
Wei SunSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
Hailu ZhuSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
Zhaoyang PanSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
Qi WangSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
Yicong WangSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
Yuanli LiuSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
Tianjia GuanSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China. guan_tianjia@163.com.

Funding

Science & Technology Fundamental Resources Investigation Program 2023FY100604
6 · The paper itself

Abstract

backgroundNitrogen dioxide (NO2), a hazardous air pollutant, has been linked to various adverse health outcomes, yet its association with serum lipid profiles - a key precursor to cardiovascular diseases and metabolic diseases - remains limited and inconsistent. Therefore, we used a nationwide prospective cohort to investigate the association between ambient NO2 exposure and serum lipid profiles.

methodsA total of 296,537 adults with 691,924 repeated visits were included. High-resolution (1 × 1 km) monthly ambient NO2 concentrations were obtained by incorporating satellite observations, chemical transport model simulations and high-resolution geographical variables. We used fixed-effect model to investigate the health effects of ambient NO2 exposure on serum lipid profiles.

resultsEach 10 µg/m3 increment of ambient NO2 exposure was related to an elevated risk of hyperbetalipoproteinemia [lag 2 month, relative risk (RR) = 1.140, 95% confidence interval (CI): 1.116–1.165], hypoalphalipoproteinemia (lag 1 month, RR = 1.082, 95%CI: 1.041–1.125) and hypercholesterolemia (lag 2 month, RR = 1.167, 95%CI: 1.139–1.196) in linear model, except for the risk of hypertriglyceridemia. Their attributable fractions were 12.31% (95%CI: 10.39%-14.19%), 7.55% (95%CI: 3.90%-11.07%) and 14.35% (95%CI: 12.22%-16.42%), respectively. The dose-response relationship in non-linear model between ambient NO2 exposure and dyslipidemia risk was an approximately inverse L-shaped nonlinear curve, with a transient risk plateau or fluctuation between 40 µg/m3 and 60 µg/m3 for hyperbetalipoproteinemia, hypoalphalipoproteinemia and hypertriglyceridemia. Significant effect modifications indicated urban residents, the elderly, and females as more susceptible subgroups. Adjusting for fine particulate matter (PM2.5) attenuated the associations, suggesting potential synergistic effects. Similar results were also found for secondary outcomes.

conclusionsOur findings demonstrate that exposure to ambient NO2 was significantly associated with elevated dyslipidemia risk, with notable spatial heterogeneity and population-specific susceptibility patterns, underscoring the need for integrated air quality management and precision public health interventions to reconcile public health protection and environmental governance.

Indexed as

Air PollutantsEnvironmental ExposureLipidsNitrogen DioxideAdultDyslipidemiasFemaleHumansLongitudinal StudiesMaleMiddle AgedProspective StudiesAir PollutantsLipidsNitrogen DioxideAssociationLipidLongitudinal studyNitrogen dioxide

Identifiers

PMID41975355
PMCPMC13195986

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.