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Sun X, Lin X, Yao J, Tian T, Li Z, Chen S, Hu W, Jiang J, Tang H, Cai H, Guo T, Chen X, Chen Z, Zhang M, Sun Y, Lin S, Qu Y, Deng X, Lin Z, Xia L, Jin Y, Zhang W. Potential causal links of long-term exposure to PM 2.5 and its chemical components with the risk of nasopharyngeal carcinoma recurrence: A 10-year cohort study in South China. Int J Cancer 2024; 155:1558-1566. [PMID: 38863244 DOI: 10.1002/ijc.35047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 04/27/2024] [Accepted: 05/10/2024] [Indexed: 06/13/2024]
Abstract
There is a lack of evidence from cohort studies on the causal association of long-term exposure to ambient fine particulate matter (PM2.5) and its chemical components with the risk of nasopharyngeal carcinoma (NPC) recurrence. Based on a 10-year prospective cohort of 1184 newly diagnosed NPC patients, we comprehensively evaluated the potential causal links of ambient PM2.5 and its chemical components including black carbon (BC), organic matter (OM), sulfate (SO4 2-), nitrate (NO3 -), and ammonium (NH4 +) with the recurrence risk of NPC using a marginal structural Cox model adjusted with inverse probability weighting. We observed 291 NPC patients experiencing recurrence during the 10-year follow-up and estimated a 33% increased risk of NPC recurrence (hazard ratio [HR]: 1.33, 95% confidence interval [CI]: 1.02-1.74) following each interquartile range (IQR) increase in PM2.5 exposure. Each IQR increment in BC, NH4 +, OM, NO3 -, and SO4 2- was associated with HRs of 1.36 (95%CI: 1.13-1.65), 1.35 (95%CI: 1.07-1.70), 1.33 (95%CI: 1.11-1.59), 1.32 (95%CI: 1.06-1.64), 1.31 (95%CI: 1.08-1.57). The elderly, patients with no family history of cancer, no smoking history, no drinking history, and those with severe conditions may exhibit a greater likelihood of NPC recurrence following exposure to PM2.5 and its chemical components. Additionally, the effect estimates of the five components are greater among patients who were exposed to high concentration than in the full cohort of patients. Our study provides solid evidence for a potential relationship between long-term exposure to PM2.5 and its components and the risk of NPC recurrence.
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Affiliation(s)
- Xurui Sun
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xiao Lin
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Jijin Yao
- The Cancer Center of the Fifth Affiliated Hospital of Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Biomedical Imaging, Zhuhai, China
| | - Tian Tian
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhiqiang Li
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Shimin Chen
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Weihua Hu
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Jie Jiang
- Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China
| | - Hui Tang
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Huanle Cai
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Tong Guo
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Xudan Chen
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Zhibing Chen
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
| | - Man Zhang
- Hospital Infection Control Office, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Yongqing Sun
- Department of Ultrasound, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
| | - Shao Lin
- Department of Environmental Health Sciences, University at Albany, State University of New York, Rensselaer, New York, USA
| | - Yanji Qu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xinlei Deng
- Analytics Department, Novartis Pharmaceuticals UK Ltd, Novartis Pharma AG, London, UK
| | - Ziqiang Lin
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
| | - Liangping Xia
- VIP Region, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Yanan Jin
- The Cancer Center of the Fifth Affiliated Hospital of Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Biomedical Imaging, Zhuhai, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Health & Research Center for Health Information & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou, China
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Hu M, Jiang C, Meng R, Luo Y, Wang Y, Huang M, Li F, Ma H. Effect of air pollution on the prevalence of breast and cervical cancer in China: a panel data regression analysis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:82031-82044. [PMID: 37318726 DOI: 10.1007/s11356-023-28068-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 05/30/2023] [Indexed: 06/16/2023]
Abstract
The association between the prevalence of breast and cervical cancer in Chinese women and air pollution is obscure. The study aims to analyze the correlation between air pollution and the prevalence of breast and cervical cancer, and whether the gross domestic product (GDP) has a modifying effect on the impact of air pollution on the prevalence of breast and cervical cancer. Extracting panel data from 31 provinces and cities between 2006 and 2020, we evaluated the association between breast and cervical cancer prevalence and pollutant emissions from 2006 to 2015 with two-way fixed-effect models. We also analyzed the interaction between GDP and pollutant emissions and further check the robustness of the moderating effect results using group regression from 2016 to 2020. Cluster robust standard errors were used to correct for the heteroskedasticity and autocorrelation. The coefficients of models show that the coefficients of logarithmic soot and dust emissions are estimated to be significantly positive, and the coefficients of their square terms are significantly negative. The robust results suggest that the relationship between soot and dust emissions and breast or cervical cancer prevalence is non-linear, from 2006 to 2015. In the analysis of particulate matter (PM) data in 2016-2020, the PM-GDP interaction term was also significantly negative, indicating that GDP growth weakened the effect of PM on the prevalence of breast cancer and cervical cancer. In provinces with higher GDP, the indirect effect of PM emissions concerning breast cancer is -0.396 while in provinces with lower GDP, it is about -0.215. The corresponding coefficient concerning cervical cancer is about -0.209 in provinces with higher GDP but not significant in provinces with lower GDP. Our results suggest that there is an inverted U-shaped relationship between the prevalence of breast cancer and cervical cancer and air pollutants from 2006 to 2015. GDP growth has a significant negative moderating effect on the impact of air pollutants on the prevalence of breast cancer and cervical cancer. PM emissions have a higher effect on the prevalence of breast and cervical cancer in provinces with higher GDP and a lower impact in provinces with lower GDP.
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Affiliation(s)
- Meiyu Hu
- Department of Public Health, Hangzhou Normal University, Yuhangtang Road, Yuhang District, 311121, Hangzhou, Zhejiang Province, China
| | - Chen Jiang
- Department of Public Health, Hangzhou Normal University, Yuhangtang Road, Yuhang District, 311121, Hangzhou, Zhejiang Province, China
| | - Runtang Meng
- Department of Public Health, Hangzhou Normal University, Yuhangtang Road, Yuhang District, 311121, Hangzhou, Zhejiang Province, China
| | - Yingxian Luo
- Department of Public Health, Hangzhou Normal University, Yuhangtang Road, Yuhang District, 311121, Hangzhou, Zhejiang Province, China
| | - Yaxin Wang
- Department of Public Health, Hangzhou Normal University, Yuhangtang Road, Yuhang District, 311121, Hangzhou, Zhejiang Province, China
| | - Mengyi Huang
- Department of Public Health, Hangzhou Normal University, Yuhangtang Road, Yuhang District, 311121, Hangzhou, Zhejiang Province, China
| | - Fudong Li
- Department of Public Health Surveillance & Advisory, Zhejiang Provincial Center for Disease Control and Prevention, Xincheng Road, Binjiang District, 310051, Hangzhou, Zhejiang, China
| | - Haiyan Ma
- Department of Public Health, Hangzhou Normal University, Yuhangtang Road, Yuhang District, 311121, Hangzhou, Zhejiang Province, China.
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Li YZ, Huang SH, Shi S, Chen WX, Wei YF, Zou BJ, Yao W, Zhou L, Liu FH, Gao S, Yan S, Qin X, Zhao YH, Chen RJ, Gong TT, Wu QJ. Association of long-term particulate matter exposure with all-cause mortality among patients with ovarian cancer: A prospective cohort. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 884:163748. [PMID: 37120017 DOI: 10.1016/j.scitotenv.2023.163748] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/19/2023] [Accepted: 04/22/2023] [Indexed: 05/03/2023]
Abstract
BACKGROUND Evidence of the association between particles with a diameter of 2.5 μm or less (PM2.5) in long term and ovarian cancer (OC) mortality is limited. METHODS This prospective cohort study analyzed data collected between 2015 and 2020 from 610 newly diagnosed OC patients, aged 18-79 years. The residential average PM2.5 concentrations 10 years before the date of OC diagnosis were assessed by random forest models at a 1 km × 1 km resolution. Cox proportional hazard models fully adjusted for the covariates (including age at diagnosis, education, physical activity, kitchen ventilation, FIGO stage, and comorbidities) and distributed lag non-linear models were used to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) of PM2.5 and all-cause mortality of OC. RESULTS During a median follow-up of 37.6 months (interquartile: 24.8-50.5 months), 118 (19.34 %) deaths were confirmed among 610 OC patients. One-year PM2.5 exposure levels before OC diagnosis was significantly associated with an increase in all-cause mortality among OC patients (single-pollutant model: HR = 1.22, 95 % CI: 1.02-1.46; multi-pollutant models: HR = 1.38, 95 % CI: 1.10-1.72). Furthermore, during 1 to 10 years prior to diagnosis, the lag-specific effect of long-term PM2.5 exposure on the all-cause mortality of OC had a risk increase for lag 1-6 years, and the exposure-response relationship was linear. Of note, significant interactions between several immunological indicators as well as solid fuel use for cooking and ambient PM2.5 concentrations were observed. CONCLUSION Higher ambient PM2.5 concentrations were associated with an increased risk of all-cause mortality among OC patients, and there was a lag effect in long-term PM2.5 exposure.
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Affiliation(s)
- Yi-Zi Li
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shu-Hong Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Wen-Xiao Chen
- Department of Sports Medicine and Joint Surgery, The People's Hospital of Liaoning Province, Shenyang, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bing-Jie Zou
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Wei Yao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lu Zhou
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Fang-Hua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shi Yan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ren-Jie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China; Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China.
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