Individual exposure of ambient particulate matters and eosinophilic chronic rhinosinusitis with nasal Polyps: Dose-Response, mediation effects and recurrence prediction

Jiajia Wang; Shen Shen; Bing Yan; Yunsheng He; Guoji Zhang; Chunguang Shan; Qintai Yang; Long Qin; Zhijian Duan; Luyun Jiang; Xin Wang; Xin Wei; Chengshuo Wang; Rui Chen; Luo Zhang

doi:10.1016/j.envint.2023.108031

Individual exposure of ambient particulate matters and eosinophilic chronic rhinosinusitis with nasal Polyps: Dose-Response, mediation effects and recurrence prediction

Environ Int. 2023 Jul:177:108031. doi: 10.1016/j.envint.2023.108031. Epub 2023 Jun 12.

Authors

Jiajia Wang¹, Shen Shen², Bing Yan², Yunsheng He³, Guoji Zhang⁴, Chunguang Shan⁵, Qintai Yang⁶, Long Qin⁷, Zhijian Duan⁸, Luyun Jiang⁹, Xin Wang¹⁰, Xin Wei¹¹, Chengshuo Wang¹², Rui Chen¹³, Luo Zhang¹⁴

Affiliations

¹ Department of Occupational and Environmental Health, School of Public Health, Capital Medical University, Beijing 100069, PR China; Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, PR China.
² Department of Otolaryngology, Head and Neck Surgery, Beijing TongRen Hospital, Capital Medical University, Beijing, PR China; Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, PR China.
³ Department of Otolaryngology, Huzhou Central Hospital, Huzhou, PR China.
⁴ Department of Otolaryngology, Baoding No.1 Central Hospital, Baoding, PR China.
⁵ Department of Otolaryngology, The Second Hospital of Hebei Medical University, Shijiazhuang, PR China.
⁶ Department of Otorhinolaryngology-Head and Neck Surgery, Department of Allergy, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
⁷ Department of Otolaryngology, The Second Affiliated Hospital of Baotou Medical College, Baotou, PR China.
⁸ Department of Otolaryngology, Hohhot First Hospital, Hohhot, PR China.
⁹ Department of Otolaryngology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu 610075, China.
¹⁰ Department of Otorhinolaryngology-Head and Neck Surgery, The People's Hospital of Suzhou New District, Suzhou, PR China.
¹¹ Department of Otolaryngology, Hainan General Hospital, Beijing, PR China.
¹² Department of Otolaryngology, Head and Neck Surgery, Beijing TongRen Hospital, Capital Medical University, Beijing, PR China; Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, PR China; Department of Allergy, Beijing TongRen Hospital, Capital Medical University, Beijing, China; Research Unit of Diagnosis and Treatment of Chronic Nasal Diseases, Chinese Academy of Medical Sciences, Beijing, PR China.
¹³ Beijing Key Laboratory of Environmental Toxicology, Capital Medical University, Beijing 100069, PR China; School of Public Health, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100069, PR China; Department of Toxicology and Sanitary Chemistry, School of Public Health, Capital Medical University, Beijing 100069, PR China. Electronic address: ruichen@ccmu.edu.cn.
¹⁴ Department of Otolaryngology, Head and Neck Surgery, Beijing TongRen Hospital, Capital Medical University, Beijing, PR China; Beijing Key Laboratory of Nasal Diseases, Beijing Institute of Otolaryngology, Beijing, PR China; Department of Allergy, Beijing TongRen Hospital, Capital Medical University, Beijing, China; Research Unit of Diagnosis and Treatment of Chronic Nasal Diseases, Chinese Academy of Medical Sciences, Beijing, PR China. Electronic address: dr.luozhang@139.com.

PMID: 37327504
DOI: 10.1016/j.envint.2023.108031

Abstract

Purpose: We evaluated the association between ambient particulate matter (PM) exposure and eosinophilic chronic rhinosinusitis with nasal polyps (CRSwNP), and predicted the CRSwNP recurrence risk using machine learning algorithms.

Methods: In total, 1,086 patients with CRSwNP were recruited from nine hospitals in China during 2014-2019. The average annual concentrations of ambient PMs before surgery were assessed using satellite-based daily concentrations of PM_2.5 and PM₁₀ for a 1 × 1-km² area. Linear regression and logistic regression models were used to evaluate the associations of PM exposure with eosinophilia and risks of eosinophilic CRSwNPs. In addition, mediation effect analysis was used to validate the interrelationships of the aforementioned factors. Finally, machine learning algorithms were used to predict the recurrence risks of CRSwNPs.

Results: There was a significantly increased risk of eosinophilic CRSwNPs with each 10 μg/m³ increase in PM_s, with odds ratios (ORs) of 1.039 (95% confidence interval [CI] = 1.007-1.073) for PM₁₀ and 1.058 (95% CI = 1.007- 1.112) for PM_2.5. Eosinophils had a significant mediation effect, which accounted for 52% and 35% of the relationships of CRSwNP recurrence with PM₁₀ and PM_2.5, respectively. Finally, we developed a naïve Bayesian model to predict the risk of CRSwNP recurrence based on PM exposure, inflammatory data, and patients' demographic factors.

Conclusions: Increased PM exposure is associated with an increased risk of eosinophilic CRSwNP in China. Therefore, patients with eosinophilic CRSwNP should reduce PM exposure to mitigate its harmful impacts.

Keywords: Chronic rhinosinusitis with nasal polyps; Eosinophils; Machine learning; Particulate matters; Prediction model.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Bayes Theorem
Chronic Disease
Eosinophilia* / complications
Eosinophilia* / surgery
Eosinophils
Humans
Nasal Polyps* / complications
Nasal Polyps* / epidemiology
Nasal Polyps* / surgery
Rhinitis* / epidemiology
Sinusitis* / complications
Sinusitis* / epidemiology
Sinusitis* / surgery