| Title: | Long-term Associations Between Time-varying Exposure to Ambient PM2.5 and Mortality: An Analysis of the UK Biobank |
| Journal: | Epidemiology |
| Published: | 22 Oct 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39435892/ |
| DOI: | https://doi.org/10.1097/ede.0000000000001796 |
Publication 13625
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Abstract
BACKGROUND: Evidence for long-term mortality risks of PM 2.5 comes mostly from large administrative studies with incomplete individual information and limited exposure definitions. Here we assess PM 2.5 -mortality associations in the UK Biobank cohort using detailed information on confounders and exposure.</p>
METHODS: We reconstructed detailed exposure histories for 498,090 subjects by linking residential data with high-resolution PM 2.5 concentrations from spatiotemporal machine-learning models. We split the time-to-event data and assigned yearly exposures over a lag window of 8 years. We fitted Cox proportional hazard models with time-varying exposure controlling for contextual- and individual-level factors, as well as trends. In secondary analyses, we inspected the lag structure using distributed lag models and compared results with alternative exposure sources and definitions.</p>
RESULTS: In fully adjusted models, an increase of 10 μg/m³ in PM 2.5 was associated with hazard ratios of 1.27 (95% confidence interval: 1.06, 1.53) for all-cause, 1.24 (1.03, 1.50) for nonaccidental, 2.07 (1.04, 4.10) for respiratory, and 1.66 (0.86, 3.19) for lung cancer mortality. We found no evidence of association with cardiovascular deaths (hazard ratio = 0.88, 95% confidence interval: 0.59, 1.31). We identified strong confounding by both contextual- and individual-level lifestyle factors. The distributed lag analysis suggested differences in relevant exposure windows across mortality causes. Using more informative exposure summaries and sources resulted in higher risk estimates.</p>
CONCLUSIONS: We found associations of long-term PM 2.5 exposure with all-cause, nonaccidental, respiratory, and lung cancer mortality, but not with cardiovascular mortality. This study benefits from finely reconstructed time-varying exposures and extensive control for confounding, further supporting a plausible causal link between long-term PM 2.5 and mortality.</p>
20 Keywords
- Adult
- Aged
- Air Pollutants
- Air Pollution
- Biological Specimen Banks
- Cardiovascular Diseases
- Cohort Studies
- Environmental Exposure
- Female
- Humans
- Machine Learning
- Male
- Middle Aged
- Mortality
- Particulate Matter
- Proportional Hazards Models
- Respiratory Tract Diseases
- Time Factors
- UK Biobank
- United Kingdom
11 Authors
- Jacopo Vanoli
- Arturo de la Cruz Libardi
- Francesco Sera
- Massimo Stafoggia
- Pierre Masselot
- Malcolm N. Mistry
- Sanjay Rajagopalan
- Jennifer K. Quint
- Chris Fook Sheng Ng
- Lina Madaniyazi
- Antonio Gasparrini
1 Application
| Application ID | Title |
|---|---|
| 56431 | Individual-level analysis on health risks associated with environmental exposures |
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