| Title: | Potential benefits in all-cause and cause-specific mortality due to separate and joint hypothetical interventions of multiple air pollutants: A parametric g-computation analysis |
| Journal: | Environmental Advances |
| Published: | 1 Dec 2025 |
| DOI: | https://doi.org/10.1016/j.envadv.2025.100668 |
Publication 16814
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Abstract
Although studies have demonstrated the adverse influence of air pollution, the optimal strategy for reducing air pollution levels to alleviate mortality burden remains elusive. With data from the UK Biobank, annual mean concentrations of five air pollutants (PM2.5, PM10, NO2, NOx, and SO2) for each participant were estimated. The parametric g-computation was applied to estimate the risk differences (RDs) in all-cause and cause-specific mortality under various air pollution intervention strategies. We implemented both dynamic threshold interventions and percentage decremental interventions (e.g., 15%, 25% decrease in concentration) for each pollutant individually (separate strategies) and for multiple pollutants simultaneously (joint strategies). During a median follow-up of 11.51 years, 22,159 (5.98%) deaths occurred among the 370,357 participants. Both separate and joint air pollution intervention strategies were significantly associated with reduced risks of all-cause and cause-specific mortality, with all-cause mortality risk reduced by up to 2.0%. Notably, joint intervention strategies contributed to greater risk reductions compared to separate interventions. For example, the RDs for cancer mortality under the joint intervention scenarios were 1.3 to 3.4 times greater than those under separate interventions when the concentrations of PM2.5, NO2, and SO2 were concurrently lowered by 35%. Our study indicates that targeting air pollution reduction could significantly reduce mortality risks. Joint intervention strategies are more highly recommended than separate intervention strategies.</p>
10 Authors
- Lan Chen
- Shengtao Wei
- Dashan Zheng
- Zhenhe Huang
- Kin-Fai Ho
- Fei Tian
- Weiyi Yang
- Wanqi Wen
- Zilong Zhang
- Hualiang Lin
1 Application
| Application ID | Title |
|---|---|
| 69550 | Identifying the potential effects of environmental and other healthcare related factors influencing health outcomes, mediated by genetic variances |
Enabling scientific discoveries that improve human health