Specifying the Associations between PM2.5 Constituents and Gastrointestinal Cancer Incidence: Findings from a Prospective Cohort Study in Beijing, China

被引:1
|
作者
Yang, Lei [1 ,2 ]
Kang, Ning [3 ]
Wang, Ning [1 ,4 ]
Zhang, Xi [1 ]
Liu, Shuo [1 ]
Li, Huichao [1 ]
Cao, Lili [1 ]
Xue, Tao [3 ,4 ,5 ,7 ]
Li, Ziyu [8 ]
Ji, Jiafu [9 ]
Zhu, Tong [5 ,6 ]
机构
[1] Peking Univ, Key Lab Carcinogenesis & Translat Res, Beijing Off Canc Prevent & Control, Minist Educ Beijing,Canc Hosp & Inst, Beijing 100142, Peoples R China
[2] Inner Mongolia Med Univ, Peking Univ Canc Hosp, Inner Mongolia Canc Ctr, Affiliated Canc Hosp, Inner Mongolia Campus, Hohhot 010020, Peoples R China
[3] Peking Univ, Inst Reprod & Child Hlth, Natl Hlth Commiss, Sch Publ Hlth Hlth Sci Ctr,Key Lab Reprod Hlth, Beijing 100191, Peoples R China
[4] Peking Univ, Sch Publ Hlth, Dept Epidemiol & Biostat,Minist Educ, Hlth Sci Ctr,Key Lab Epidemiol Major Dis PKU, Beijing 100191, Peoples R China
[5] Peking Univ, Ctr Environm & Hlth, State Environm Protect Key Lab Atmospher Exposure, Beijing 100871, Peoples R China
[6] Peking Univ, Coll Environm Sci & Engn, Beijing 100871, Peoples R China
[7] Peking Univ, Adv Inst Informat Technol, Hangzhou 311215, Peoples R China
[8] Peking Univ, Gastrointestinal Canc Ctr, Key Lab Carcinogenesis & Translat Res, Minist Educ Beijing,Canc Hosp & Inst, Beijing 100142, Peoples R China
[9] Peking Univ, Gastrointestinal Canc Ctr, State Key Lab Holist Integrat Management Gastroint, Beijing Key Lab Carcinogenesis & Translat Res,Canc, Beijing 100142, Peoples R China
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
Ambient air pollution; mixture exposure; explainablemachine learning model; cohort study; AIR-POLLUTION; EXPOSURE; MORTALITY;
D O I
10.1021/acs.est.4c10986
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study aimed to test the association between PM2.5 and the incidence of gastrointestinal (GI) cancer, and further to detect the primary constituents on this association. A sum of 142,982 participants without GI cancer at baseline were derived from the National Urban Cancer Screening Program in Beijing (2013-2019). The 5 year averaged concentrations of PM2.5 mass and its five constituents, namely, black carbon (BC), ammonium (NH4 +), nitrate (NO3 -), organic matter (OM), and inorganic sulfate (SO4 2-), were estimated by using a hybrid machine learning model. The Cox proportional hazard model with fixed effects was used to explore the associations between PM2.5 mass and its constituents with the incidence of GI cancer. The double-exposure linear model, the mixture exposure model of quantile-based g-computation, and an explainable machine learning model were utilized to evaluate the importance of different PM2.5 constituents. Long-term exposure to PM2.5 mass and its constituents was linearly associated with GI cancer; the estimated hazard ratio and 95% confidence interval (95% CI) of per standard deviation increment were 1.367 (95% CI: 1.257 to 1.487) for PM2.5 mass, 1.434 (95% CI: 1.307 to 1.574) for BC, 1.255 (95% CI: 1.169 to 1.349) for NH4 +, 1.217 (95% CI: 1.139 to 1.301) for NO3 -, 1.410 (95% CI: 1.287 to 1.546) for OM, and 1.410 (95% CI: 1.288 to 1.542) for SO4 2-. By using multiple methods, results indicated that SO4 2- and BC were the most important constituents. Results indicated that long-term exposure to PM2.5 was associated with a high incidence of GI cancer, and BC and SO4 2- were robustly identified as the primary constituents.
引用
收藏
页码:21489 / 21498
页数:10
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