Yang Lei, Kang Ning, Wang Ning, Zhang Xi, Liu Shuo, Li Huichao, Cao Lili, Xue Tao, Li Ziyu, Ji Jiafu, Zhu Tong
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China.
Peking University Cancer Hospital (Inner Mongolia Campus)/Affiliated Cancer Hospital of Inner Mongolia Medical University, Inner Mongolia Cancer Center, Hohhot 010020, China.
Environ Sci Technol. 2024 Dec 10;58(49):21489-21498. doi: 10.1021/acs.est.4c10986. Epub 2024 Dec 2.
This study aimed to test the association between PM 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 PM mass and its five constituents, namely, black carbon (BC), ammonium (NH), nitrate (NO), organic matter (OM), and inorganic sulfate (SO), were estimated by using a hybrid machine learning model. The Cox proportional hazard model with fixed effects was used to explore the associations between PM 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 PM constituents. Long-term exposure to PM 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 PM mass, 1.434 (95% CI: 1.307 to 1.574) for BC, 1.255 (95% CI: 1.169 to 1.349) for NH, 1.217 (95% CI: 1.139 to 1.301) for NO, 1.410 (95% CI: 1.287 to 1.546) for OM, and 1.410 (95% CI: 1.288 to 1.542) for SO. By using multiple methods, results indicated that SO and BC were the most important constituents. Results indicated that long-term exposure to PM was associated with a high incidence of GI cancer, and BC and SO were robustly identified as the primary constituents.
本研究旨在测试细颗粒物(PM)与胃肠道(GI)癌发病率之间的关联,并进一步检测该关联中的主要成分。共有142,982名在基线时无胃肠道癌的参与者来自北京国家城市癌症筛查项目(2013 - 2019年)。通过使用混合机器学习模型估算了PM质量及其五种成分(即黑碳(BC)、铵(NH)、硝酸盐(NO)、有机物(OM)和无机硫酸盐(SO))的5年平均浓度。采用固定效应的Cox比例风险模型来探究PM质量及其成分与胃肠道癌发病率之间的关联。利用双暴露线性模型、基于分位数的g计算混合暴露模型和可解释机器学习模型来评估不同PM成分的重要性。长期暴露于PM质量及其成分与胃肠道癌呈线性相关;每标准差增加的估计风险比和95%置信区间(95%CI)分别为:PM质量为1.367(95%CI:1.257至1.487),BC为1.434(95%CI:1.307至1.574),NH为1.255(95%CI:1.169至1.349),NO为1.217(95%CI:1.139至1.301),OM为1.410(95%CI:1.287至1.546),SO为1.410(95%CI:1.288至1.542)。通过多种方法,结果表明SO和BC是最重要的成分。结果表明,长期暴露于PM与胃肠道癌的高发病率相关,并且BC和SO被有力地确定为主要成分。