Air pollution exposure modes, smoking and genetic risk with chronic respiratory diseases: a prospective study

Previous studies often focused on single pollutant source, failing to replicate real-world exposure scenarios for chronic respiratory disease (CRD) risk. We aimed to explore the mixed exposure patterns of CRD risk factors and investigate interactions with smoking and genetic risk. We identified air pollution exposure modes using latent class analysis (LCA) in the UK Biobank. Cox model assessed associations between exposure modes and lung cancer (LC), idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD) and asthma. Interactions among exposure modes, smoking and genetic risk were analyzed. LCA divided participants into five groups, and hazard ratios (HRs) for "High air pollution" group were 1.28 for LC (95% CI: 1.08-1.52), 1.23 for IPF (95% CI: 1.03-1.48), 1.28 for COPD (95% CI: 1.17-1.39) and 1.09 for asthma (95% CI: 1.01-1.18). Significant additive interactions between high air pollution and smoking were observed for LC and COPD. Individuals with high genetic risk exposed to both smoking and high air pollution showed the relative excess risk due to interaction (RERI) of 2.74 for LC, 3.93 for IPF, and 1.68 for COPD. Smoking and air pollution together accounted for over 40% of LC, IPF and COPD cases. Our findings highlight the complex interplay between environmental air pollution, smoking, and genetic risk in CRD development in real-world exposure scenarios.

Authors

Institutions

Publication Details

Journal
npj Primary Care Respiratory Medicine
Published
2025-12-05
DOI
https://doi.org/10.1038/s41533-025-00469-z
Primary Topic
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Air pollution exposure modes, smoking and genetic risk with chronic respiratory diseases: a prospective study

Lang Lyu, Weiwei Duan, Ru Yuan, Lei Lei et al.
npj Primary Care Respiratory Medicine
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
article

Air pollution exposure modes, smoking and genetic risk with chronic respiratory diseases: a prospective study

Lang Lyu, Weiwei Duan, Ru Yuan, Lei Lei, Ting Wang, Fanqing Meng, Meng Zhu
article en

Abstract

Previous studies often focused on single pollutant source, failing to replicate real-world exposure scenarios for chronic respiratory disease (CRD) risk. We aimed to explore the mixed exposure patterns of CRD risk factors and investigate interactions with smoking and genetic risk. We identified air pollution exposure modes using latent class analysis (LCA) in the UK Biobank. Cox model assessed associations between exposure modes and lung cancer (LC), idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD) and asthma. Interactions among exposure modes, smoking and genetic risk were analyzed. LCA divided participants into five groups, and hazard ratios (HRs) for "High air pollution" group were 1.28 for LC (95% CI: 1.08-1.52), 1.23 for IPF (95% CI: 1.03-1.48), 1.28 for COPD (95% CI: 1.17-1.39) and 1.09 for asthma (95% CI: 1.01-1.18). Significant additive interactions between high air pollution and smoking were observed for LC and COPD. Individuals with high genetic risk exposed to both smoking and high air pollution showed the relative excess risk due to interaction (RERI) of 2.74 for LC, 3.93 for IPF, and 1.68 for COPD. Smoking and air pollution together accounted for over 40% of LC, IPF and COPD cases. Our findings highlight the complex interplay between environmental air pollution, smoking, and genetic risk in CRD development in real-world exposure scenarios.

npj Primary Care Respiratory MedicineVol. 36(1)
Xuzhou Medical College (CN), Nanjing Drum Tower Hospital (CN), Jiangsu Cancer Hospital (CN), Nanjing Medical University (CN)
National Natural Science Foundation of China, Nanjing University, Natural Science Research of Jiangsu Higher Education Institutions of China
Openalex Percentile: Top 43%
Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
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.