Abstract：
BACKGROUND: Evidence of a potential causal link between long-term exposure to particulate matter (PM) and all-site cancer mortality from large population cohorts remained limited and suffered from residual confounding issues with traditional statistical methods.
OBJECTIVE: We aimed to examine the potential causal relationship between long-term PM exposure and all-site cancer mortality in South China using causal inference methods.
METHODS: We used a cohort in southern China that recruited 580,757 participants from 2009 through 2015 and tracked until 2020. Annual averages of PM1, PM2.5, and PM10 concentrations were generated with validated spatiotemporal models. We employed a causal inference approach, the Marginal Structural Cox model, based on observational data to evaluate the association between long-term exposure to PM and all-site cancer mortality.
RESULTS: With an increase of 1 µg/m³ in PM1, PM2.5, and PM10, the hazard ratios (HRs) and 95% confidence interval (CI) for all-site cancer were 1.033 (95% CI: 1.025-1.041), 1.032 (95% CI: 1.027-1.038), and 1.020 (95% CI: 1.016-1.025), respectively. The HRs (95% CI) for digestive system and respiratory system cancer mortality associated with each 1 µg/m³ increase in PM1 were 1.022 (1.009-1.035) and 1.053 (1.038-1.068), respectively. In addition, inactive participants, who never smoked, or who lived in areas of low surrounding greenness were more susceptible to the effects of PM exposure, the HRs (95% CI) for all-site cancer mortality were 1.042 (1.031-1.053), 1.041 (1.032-1.050), and 1.0473 (1.025-1.070) for every 1 µg/m³ increase in PM1, respectively. The effect of PM1 tended to be more pronounced in the low-exposure group than in the general population, and multiple sensitivity analyses confirmed the robustness of the results.
CONCLUSIONS: This study provided evidence that long-term exposure to PM may elevate the risk of all-site cancer mortality, emphasizing the potential health benefits of improving air quality for cancer prevention.
OBJECTIVE: We aimed to examine the potential causal relationship between long-term PM exposure and all-site cancer mortality in South China using causal inference methods.
METHODS: We used a cohort in southern China that recruited 580,757 participants from 2009 through 2015 and tracked until 2020. Annual averages of PM1, PM2.5, and PM10 concentrations were generated with validated spatiotemporal models. We employed a causal inference approach, the Marginal Structural Cox model, based on observational data to evaluate the association between long-term exposure to PM and all-site cancer mortality.
RESULTS: With an increase of 1 µg/m³ in PM1, PM2.5, and PM10, the hazard ratios (HRs) and 95% confidence interval (CI) for all-site cancer were 1.033 (95% CI: 1.025-1.041), 1.032 (95% CI: 1.027-1.038), and 1.020 (95% CI: 1.016-1.025), respectively. The HRs (95% CI) for digestive system and respiratory system cancer mortality associated with each 1 µg/m³ increase in PM1 were 1.022 (1.009-1.035) and 1.053 (1.038-1.068), respectively. In addition, inactive participants, who never smoked, or who lived in areas of low surrounding greenness were more susceptible to the effects of PM exposure, the HRs (95% CI) for all-site cancer mortality were 1.042 (1.031-1.053), 1.041 (1.032-1.050), and 1.0473 (1.025-1.070) for every 1 µg/m³ increase in PM1, respectively. The effect of PM1 tended to be more pronounced in the low-exposure group than in the general population, and multiple sensitivity analyses confirmed the robustness of the results.
CONCLUSIONS: This study provided evidence that long-term exposure to PM may elevate the risk of all-site cancer mortality, emphasizing the potential health benefits of improving air quality for cancer prevention.
摘要：
背景：长期暴露于颗粒物（PM）与来自大人群队列的全部位癌症死亡率之间潜在因果关系的证据仍然有限，并且传统统计方法存在残留的混杂问题。
目的：我们的目的是利用因果推断方法研究中国南方长期PM暴露与全部位癌症死亡率之间的潜在因果关系。
方法：我们使用了中国南方的一个队列，从2009年到2015年招募了580,757名参与者，并跟踪到2020年。使用经过验证的时空模型生成了PM1，PM2.5和PM10浓度的年平均值。我们采用了因果推断方法，边际结构Cox模型，基于观察性数据评估长期暴露于PM与全部位癌症死亡率之间的关联.
结果：随着PM1，PM2.5和PM10的增加1µg/m3，所有部位癌症的风险比（HR）和95％置信区间（CI）为1.033（95％CI：1.025-1.041），1.032（95%CI：1.027-1.038），和1.020（95%CI：1.016-1.025），分别。与PM1每增加1µg/m3相关的消化系统和呼吸系统癌症死亡率的HR（95％CI）为1.022（1.009-1.035）和1.053（1.038-1.068），分别。此外,不活跃的参与者,从不吸烟的人，或者居住在周围绿色度较低的地区的人更容易受到PM暴露的影响，全部位癌症死亡率的HR（95%CI）为1.042（1.031-1.053），1.041（1.032-1.050），和1.0473（1.025-1.070），分别为PM1每增加1µg/m3。PM1的影响在低暴露组中比在一般人群中更明显，多重敏感性分析证实了结果的稳健性。
结论：这项研究提供了证据，表明长期暴露于PM可能会增加所有部位癌症死亡的风险，强调改善空气质量对预防癌症的潜在健康益处。
目的：我们的目的是利用因果推断方法研究中国南方长期PM暴露与全部位癌症死亡率之间的潜在因果关系。
方法：我们使用了中国南方的一个队列，从2009年到2015年招募了580,757名参与者，并跟踪到2020年。使用经过验证的时空模型生成了PM1，PM2.5和PM10浓度的年平均值。我们采用了因果推断方法，边际结构Cox模型，基于观察性数据评估长期暴露于PM与全部位癌症死亡率之间的关联.
结果：随着PM1，PM2.5和PM10的增加1µg/m3，所有部位癌症的风险比（HR）和95％置信区间（CI）为1.033（95％CI：1.025-1.041），1.032（95%CI：1.027-1.038），和1.020（95%CI：1.016-1.025），分别。与PM1每增加1µg/m3相关的消化系统和呼吸系统癌症死亡率的HR（95％CI）为1.022（1.009-1.035）和1.053（1.038-1.068），分别。此外,不活跃的参与者,从不吸烟的人，或者居住在周围绿色度较低的地区的人更容易受到PM暴露的影响，全部位癌症死亡率的HR（95%CI）为1.042（1.031-1.053），1.041（1.032-1.050），和1.0473（1.025-1.070），分别为PM1每增加1µg/m3。PM1的影响在低暴露组中比在一般人群中更明显，多重敏感性分析证实了结果的稳健性。
结论：这项研究提供了证据，表明长期暴露于PM可能会增加所有部位癌症死亡的风险，强调改善空气质量对预防癌症的潜在健康益处。
