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Association between exposure to air pollutants and the risk of inflammatory bowel diseases visits

Abstract

The topic of inflammatory bowel disease (IBD) has attracted more and more attention. Accumulating evidence suggests that exposure to air pollutants is associated with IBD, yet the results are inconsistent and study about daily exposure is few. This study evaluated the association between daily air pollution and IBD in Hefei, China. Daily IBD admission data were obtained from two hospitals in Hefei from January 1, 2019, to December 31, 2019. Daily concentrations of major air pollutants were provided by the Hefei Environmental Protection Bureau. Meteorological data were collected from China Meteorological Data Network. Distributed lag nonlinear model (DLNM) considering both the lag effects of exposure factors and nonlinear relationship of exposure-reaction was used to assess the effect of daily air pollutants exposure on IBD admission. During the study period, totally 886 cases of IBD were recruited, including 313 cases of ulcerative colitis (UC) and 573 cases of Crohn’s disease (CD). The findings showed PM2.5, O3, and CO exposure significantly increased the risk of IBD. Mean concentrations of PM2.5, O3, and CO in Hefei were 43.85ug/m3, 100.78ug/m3, and 0.76 mg/m3, respectively. Each increase of 10 mg/m3 in PM2.5/O3 and 0.1 mg/m3 in CO increased the risk of IBD. The strongest effects of these three pollutants on IBD were observed in lag2-lag3 (RR = 1.037, 95% CI: 1.005–1.070%), lag3 (RR = 1.020, 95% CI: 1.002–1.038%), and lag2 (RR = 1.036, 95% CI: 1.003–1.071%), respectively. In warm seasons, PM2.5, O3, and CO had a stronger effect increased the risk of IBD, which were observed in lag2 (RR = 1.104, 95% CI: 1.032–1.181%), lag2 and lag5 (RR = 1.023, 95% CI: 1.002–1.044%; RR = 1.036, 95% CI: 1.004–1.069%), and lag2 (RR = 1.071, 95% CI: 1.012–1.133%), respectively. Air pollutant (PM2.5, O3, and CO) exposure could increase the risk of IBD, while the most susceptibility seasons for the exposure were mainly in warm seasons. The results of this study suggest that air pollutants increase the risk of IBD patients in Hefei, China, providing a basis for developing countries to improve effective prevention of IBD, and a potential opportunity to avoid part of the risk of the onset or recurrence of IBD. This study contributes to the knowledge of the association between air pollution and IBD, but the associations need to be verified by further studies.

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Data availability

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Abbreviations

IBD:

Inflammatory bowel disease

DLNM:

Distributed lag nonlinear model

UC:

Ulcerative colitis

CD:

Crohn’s disease

CO:

Carbon monoxide

NO2 :

Nitrogen dioxide

SO2 :

Sulfur dioxide

PM2.5 :

Particulate matter with aerodynamic equivalent diameter < 2.5 μm

PM:

Particulate matter

O3 :

Ozone

PM10 :

Particulate matter with aerodynamic equivalent diameter < 10 μm

RR:

Relative risk

CI:

Confidence interval

ROS:

Reactive oxygen species

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Funding

This work was supported by the Research Foundation of Anhui Medical University (No. 2019xkj133).

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Authors

Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Siwen Ding and Shu Sun. The first draft of the manuscript was written by Siwen Ding. The manuscript was reviewed and edited by Rui Ding, Shasha Song, and Yi Cao. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Lijiu Zhang is the corresponding author and acts on behalf of all authors to ensure the accuracy or completeness of any part of the work.

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Correspondence to Lijiu Zhang.

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Ding, S., Sun, S., Ding, R. et al. Association between exposure to air pollutants and the risk of inflammatory bowel diseases visits. Environ Sci Pollut Res 29, 17645–17654 (2022). https://doi.org/10.1007/s11356-021-17009-0

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Keywords

  • Inflammatory bowel diseases
  • Air pollution
  • PM2.5
  • O3
  • CO
  • Distributed lag nonlinear model
  • Time series study