| Title: | Association between long-term exposure to low level air pollutants and incident end-stage kidney disease in the UK Biobank: A prospective cohort |
| Journal: | Chemosphere |
| Published: | 10 Jul 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37437622/ |
| DOI: | https://doi.org/10.1016/j.chemosphere.2023.139470 |
Publication 10257
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Abstract
BACKGROUND: Previous studies suggest that air pollution can increase the risk of incident chronic kidney disease (CKD). However, the association between end-stage kidney disease (ESKD) and co-exposure to relatively low-level air pollutants remains unclear.</p>
METHODS: A prospective cohort was designed based on UK Biobank. From 1 January 2010 to 12 November 2021, 453,347 participants were followed up over a median of 11.87 years. Principal component analysis was used to identify major patterns of five air pollutants, including PM2.5, PM2.5-10, PM10, NO2, and NOx. Sub-distribution hazards models were used to estimate the associations between air pollution, individually or jointly, and incident ESKD, CKD, and all-cause death, respectively.</p>
RESULTS: Principal component analysis identified two principal components, namely RC1 (PM2.5, NO2, and NOx) and RC2 (PM2.5-10 and PM10). An elevated risk of incident ESKD was associated with an interquartile range (IQR) increase in PM2.5 (hazard ratio: 1.11, 95% confidence interval: 1.02-1.22), NO2 (1.16, 1.04-1.30), NOx (1.08, 1.00-1.17), and RC1 (1.12, 1.02-1.23). An elevated risk of incident CKD was associated with an IQR increase in PM2.5 (1.05, 1.03-1.07), NO2 (1.04, 1.02-1.06), NOx (1.03, 1.02-1.05), and RC1 (1.04, 1.02-1.06). An increased risk of all-cause mortality was associated with an IQR increase in PM2.5 (1.02, 1.00-1.04). Restricted cubic spline analyses indicated a monotonic elevating association of PM2.5, NO2, NOx, and RC1 with ESKD incidence.</p>
CONCLUSIONS: Long-term exposure to PM2.5, NO2, NOx, and their complex was associated with elevated ESKD incidence, even at relatively lower levels of air pollution.</p>
10 Authors
- Jing Li
- Liang Dai
- Xiaowei Deng
- Jingwen Zhang
- Congying Song
- Junjie Xu
- Anxin Wang
- Zuying Xiong
- Ying Shan
- Xiaoyan Huang
1 Application
| Application ID | Title |
|---|---|
| 73684 | Identifying risk factors of complex diseases: observational and genetic associations |
Enabling scientific discoveries that improve human health