您的位置：山东大学 -> 科技期刊社 -> 《山东大学学报（医学版）》

山东大学学报 (医学版) ›› 2022, Vol. 60 ›› Issue (8): 115-119.doi: 10.6040/j.issn.1671-7554.0.2022.0339

• 公共卫生与管理学 • 上一篇    下一篇

绿色覆盖与癌症发病的因果关联分析

吴新莹1,2,冯一平1,2,常开锋3,贾贤杰4,薛付忠1,2   

  1. 1.山东大学齐鲁医学院公共卫生学院生物统计学系, 山东 济南 250012;2.山东大学健康医疗大数据研究院, 山东 济南 250002;3.平邑县疾病预防控制中心传染病防制科, 山东 临沂 273300;4.蚌埠医学院公共卫生学院流行病与卫生统计学教研室, 安徽 蚌埠 233000
  • 发布日期:2022-07-27
  • 通讯作者: 薛付忠. E-mail:xuefzh@sdu.edu.cn
  • 基金资助:
    国家重点研发计划(2020YFC2003500);国家自然科学基金(81773547,82173625)

Causal association between green space and cancer incidence

WU Xinying1,2, FENG Yiping1,2, CHANG Kaifeng3, JIA Xianjie4, XUE Fuzhong1,2   

  1. 1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. Institute for Medical Dataology, Cheeloo College of Medicine, Shandong University, Jinan 250002, Shandong, China;
    3. Infectious Disease Control Department, Pingyi Center for Disease Control and Prevention, Linyi 273300, Shandong, China;
    4. Department of Epidemiology and Health Statistics, School of Public Health, Bengbu Medical College, Bengbu 233000, Anhui, China
  • Published:2022-07-27

PDF (PC)

117

摘要： 目的 探讨绿色覆盖与癌症发病之间的因果关联。 方法 依托山东省健康医疗大数据平台,将平邑县居民电子健康档案、癌症监测数据和电子病历数据进行关联,构建癌症发病队列。以卫星遥感数据来源的归一化植被指数(NDVI)作为暴露指标,以癌症发病作为结局,首先采用广义线性混合模型(GLMM)探索绿色覆盖与癌症发病的关联关系,然后利用基于时间序列的阴性对照暴露(NCE-TS)方法进行因果关联分析。 结果 队列共纳入917 450人。2012~2015年平邑县共发生癌症9 157例,累积发病率为9.98‰。GLMM结果显示,NDVI每增加0.01,整体癌症发病风险降低26.42%(OR=0.7358,95%CI: 0.6417~0.8298);NCE-TS结果显示,与低水平NDVI区域相比,高水平NDVI区域的人群整体癌症的因果绝对风险降低2.651%(95%CI:-2.745%~-2.564%),肺癌、胃癌、食管癌、肝癌、结直肠癌、乳腺癌和宫颈癌的绝对风险降低0.147%~0.718%。 结论 绿色覆盖与癌症发病之间存在保护性因果关联,在癌症一级预防中应重视绿色覆盖这一生态环境要素。

关键词: 绿色覆盖, 癌症, 阴性对照暴露, 因果关联, 发病

Abstract: Objective To investigate the causal association between green space and cancer incidence. Methods Based on the Health Care Big Data Platform of Shandong Province, resident electronic health records, cancer surveillance data and electronic medical record data of Pingyi County were linked to construct a cancer incidence cohort. Green space exposure was assessed using normalized difference vegetation index(NDVI)derived from satellite remote sensing data. Outcome was defined as the diagnosis of cancer. The association between NDVI and cancer incidence was explored using generalized linear mixed model(GLMM). Negative control exposure based on time-series studies(NCE-TS)method was used to estimate the causal association. Results A total of 917,450 subjects were included in this study, and 9,157 cancer cases were reported during 2012 and 2015, with a cumulative incidence rate of 9.98‰. GLMM results showed that every 0.01 increase in NDVI was associated with a 26.42% reduction in all-sites cancer(OR=0.7358, 95%CI: 0.6417~0.8298). NCE-TS analysis showed that the causal absolute risk of all-sites cancer among population living in high-level NDVI areas was reduced by 2.651%(95%CI: -2.745%~-2.564%), compared with the low-level NDVI areas. And the absolute risk of lung cancer, stomach cancer, esophageal cancer, liver cancer, colorectal cancer, breast cancer and cervical cancer was reduced by 0.147%~0.718%. Conclusion There is a protective causal association between green space and cancer. As an important ecological environment element, green space should arouse attention in the primary prevention of cancer.

Key words: Green space, Cancer, Negative control exposure, Causal association, Incidence

中图分类号: 

  • R181.3
[1] 陈宏达, 郑荣寿, 王乐, 等. 2019年中国肿瘤流行病学研究进展[J]. 中华疾病控制杂志, 2020, 24(4): 373-379. CHEN Hongda, ZHENG Rongshou, WANG Le, et al. Progress in cancer epidemiology research in China in 2019 [J]. Chinese Journal of Disease Control & Prevention, 2020, 24(4): 373-379.
[2] 韩仁强, 周金意, 张思维, 等. 2015年中国脑瘤发病与死亡分析[J]. 中国肿瘤, 2021, 30(1): 29-34. HAN Renqiang, ZHOU Jinyi, ZHANG Siwei, et al. Incidence and mortality of brain tumor in China, 2015 [J]. China Cancer, 2021, 30(1): 29-34.
[3] Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries [J]. CA Cancer J Clin, 2021, 71(3): 209-249.
[4] Cao W, Chen HD, Yu YW, et al. Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020[J]. Chin Med J(Engl), 2021, 134(7): 783-791.
[5] Zhou M, Wang H, Zeng X, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017 [J]. Lancet, 2019, 394(10204): 1145-1158.
[6] 曹毛毛, 陈万青. 中国恶性肿瘤流行情况及防现状[J]. 中国肿瘤临床, 2019, 46(3): 145-149. CAO Maomao, CHEN Wanqing. Epidemiology of cancer in China and the current status of prevention and control [J]. Chinese Journal of clinical oncology, 2019, 46(3): 145-149.
[7] Vineis P, Wild CP. Global cancer patterns: causes and prevention [J]. Lancet, 2014, 383(9916): 549-557.
[8] Sun D, Li H, Cao M, et al. Cancer burden in China: trends, risk factors and prevention [J]. Cancer Biol Med, 2020, 17(4): 879-895.
[9] Jagai JS, Messer LC, Rappazzo KM, et.al. County-level cumulative environmental quality associated with cancer incidence [J]. Cancer, 2017, 123(15): 2901-2908.
[10] Markevych I, Schoierer J, Hartig T, et al. Exploring pathways linking greenspace to health: theoretical and methodological guidance [J]. Environ Res, 2017, 158: 301-317. doi: 10.1016/j.envres.2017.06.028.
[11] 屠星月, 黄甘霖, 邬建国.城市绿地可达性和居民福祉关系研究综述[J]. 生态学报, 2019, 39(2): 421-431. TU Xingyue, HUANG Ganlin, WU Jianguo. Review of the relationship between urban greenspace accessibility and human well-being [J]. Acta Ecologica Sinica, 2019, 39(2): 421-431.
[12] Wu KS, Huo X, Zhu GH. Relationships between esophageal cancer and spatial environment factors by using Geographic Information System [J]. Sci Total Environ, 2008, 393(2-3): 219-225.
[13] Wang L, Zhao X, Xu W, Tang J, Jiang X. Correlation analysis of lung cancer and urban spatial factor: based on survey in Shanghai [J]. J Thorac Dis, 2016, 8(9): 2626-2637.
[14] OCallaghan-Gordo C, Kogevinas M, Cirach M, et al. Residential proximity to green spaces and breast cancer risk: The multicase-control study in Spain(MCC-Spain)[J]. Int J Hyg Environ Health, 2018, 221(8): 1097-1106.
[15] Zare Sakhvidi MJ, Yang J, Siemiatycki J, et al. Greenspace exposure and cancer incidence: A 27-year follow-up of the French GAZEL cohort [J]. Sci Total Environ, 2021, 787: 147553. doi:10.1016/j.scitotenv.2021.147553.
[16] Demoury C, Thierry B, Richard H, et al. Residential greenness and risk of prostate cancer: A case-control study in Montreal, Canada [J]. Environ Int, 2017, 98: 129-136. doi:10.1016/j.envint.2016.10.024
[17] Porcherie M, Linn N, Le Gall AR, et al. Relationship between Urban Green Spaces and Cancer: A Scoping Review [J]. Int J Environ Res Public Health, 2021, 18(4): 1751. doi:10.3390/ijerph18041751.
[18] Yu Y, Li H, Sun X, et al. Identification and estimation of causal effects using a negative-control exposure in time-series studies with applications to environmental epidemiology [J]. Am J Epidemiol, 2021,190(3): 468-476.
[19] 易玲, 熊利亚, 杨小唤. 基于GIS技术的GDP空间化处理方法[J]. 甘肃科学学报, 2006, 18(2): 54-58. YI Ling, XIONG Liya, YANG Xiaohuan. Method of pixelizing GDP data based on the GIS [J]. Journal of Gansu Sciences, 2006, 18(2): 54-58.
[20] Wei J, Li ZQ, Lyapustin A, et al. Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications [J]. Remote Sensing of Environment, 2021, 252: 112136. doi:10.1016/j.rse.2020.112136.
[21] 周婷, 兰蓝, 邱建青, 等. GEE、GLMM和MLM分析卫生重复测量资料的效果比较[J]. 现代预防医学, 2017, 44(16): 2881-2885+2899. ZHOU Ting, LAN Lan, QIU Jianqing, et al. Effect comparison of GEE, GLMM, and MLM in analyzing repeated measures of health-related field [J]. Modern Preventive Medicine, 2017, 44(16): 2881-2885+2899.
[22] Bishehsari F, Mahdavinia M, Vacca M, et al. Epidemiological transition of colorectal cancer in developing countries: environmental factors, molecular pathways, and opportunities for prevention [J]. World J Gastroenterol, 2014, 20(20): 6055-6072.
[23] 王兰, 廖舒文, 赵晓菁. 健康城市规划路径与要素辨析[J]. 国际城市规划, 2016, 31(4): 4-9. WANG Lan, LIAO Shuwen, ZHAO Xiaojing. Exploration of approaches and factors of healthy city planning [J]. Urban Planning International, 2016, 31(4): 4-9.
[24] Datzmann T, Markevych I, Trautmann F, et al. Outdoor air pollution, green space, and cancer incidence in Saxony: a semi-individual cohort study [J]. BMC Public Health, 2018, 18(1): 715. doi: 10.1186/s12889-018-5615-2.
[25] 董玉萍, 刘合林, 齐君. 城市绿地与居民健康关系研究进展[J]. 国际城市规划, 2020, 35(5): 70-79. DONG Yuping, LIU Helin, QI Jun. Progress of studies on the relationship between urban green space and public health [J]. Urban Planning International, 2020, 35(5): 70-79.
[26] Huang Y, Zhu M, Ji M, et al. Air pollution, genetic factors, and the risk of lung cancer: a prospective study in the UK biobank [J]. Am J Respir Crit Care Med, 2021, 204(7): 817-825.
[27] Eckerling A, Ricon-Becker I, Sorski L, et al. Stress and cancer: mechanisms, significance and future directions [J]. Nat Rev Cancer, 2021, 21(12): 767-785.
[28] McTiernan A, Friedenreich CM, Katzmarzyk PT, et al. Physical activity in cancer prevention and survival: a systematic review [J]. Med Sci Sports Exerc, 2019, 51(6): 1252-1261.
[29] Rhew IC, Vander Stoep A, Kearney A, et al. Validation of the normalized difference vegetation index as a measure of neighborhood greenness[J]. Ann Epidemiol, 2011, 21(12): 946-952.
[1] 吴瑞芳,李长忠. 女性生育力保护的现状与进展[J]. 山东大学学报 (医学版), 2022, 60(9): 1-7.
[2] 王国云,潘臧钰. 子宫腺肌病动物模型研究进展[J]. 山东大学学报 (医学版), 2022, 60(7): 48-55.
[3] 郭孙伟,刘惜时. 子宫腺肌病发病机制和病理生理研究进展[J]. 山东大学学报 (医学版), 2022, 60(7): 6-19.
[4] 侯茹男,邵頔,秦廷廷,尚美美,申玉珍,孙晓杰. 山东省癌症患者烟草使用情况及影响因素分析[J]. 山东大学学报 (医学版), 2022, 60(6): 102-106.
[5] 郑昊天,王光辉,赵小刚,王亚东,曾榆凯,杜贾军. 基于数据库LKB1突变肺腺癌DNA异常甲基化位点构建的预后风险模型[J]. 山东大学学报 (医学版), 2022, 60(3): 51-58.
[6] 翟一凡,王兆军,白硕鑫,林少倩,王方怡,杜爽,王志萍. 孕期PM10和PM2.5暴露对新生儿出生体质量的影响[J]. 山东大学学报 (医学版), 2021, 59(8): 99-106.
[7] 罗湘杭,周若玙. 骨质疏松的病因及发病机制研究进展[J]. 山东大学学报 (医学版), 2021, 59(6): 10-14.
[8] 温红玲,徐小莹. 新发突发病毒性传染病防控与生物安全[J]. 山东大学学报 (医学版), 2021, 59(5): 40-45.
[9] 李林童,侯新国,秦君,梁凯,任建民. 青年人中的成年发病型糖尿病13型1例报道[J]. 山东大学学报 (医学版), 2020, 58(6): 71-75.
[10] 王振东,丁稳稳,凤志慧. 癫痫人群丙戊酸暴露与癌症发生风险的相关性分析[J]. 山东大学学报 (医学版), 2020, 58(4): 110-117.
[11] 刘冠邑,杨丽媛,付振涛,徐爱强,郭晓雷. 2014年山东省口腔癌发病和死亡水平分析[J]. 山东大学学报 (医学版), 2019, 57(7): 102-107.
[12] 周道斌,张炎. 原发性中枢神经系统淋巴瘤诊治现状及进展[J]. 山东大学学报 (医学版), 2019, 57(7): 31-39.
[13] 杨玉霞,臧素洁,冷安丽,王健. 以5种癌症患者住院费用为例探讨其药占比及医保支付[J]. 山东大学学报 (医学版), 2019, 57(4): 113-118.
[14] 朱爱国,马振敕,王健. 利用上皮源性卵巢癌预后的多基因信息建立预测预后模型[J]. 山东大学学报 (医学版), 2019, 57(10): 80-85.
[15] 华星星,孙晓杰,赵德利,刘卫东,倪志松,邹跃威,马仲锋,姚能亮,王家林,王海鹏. 山东省5县癌症患者治疗方式和医疗费用及其相关性分析[J]. 山东大学学报 (医学版), 2018, 56(6): 69-75.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] 索东阳,申飞,郭皓,刘力畅,杨惠敏,杨向东. Tim-3在药物性急性肾损伤动物模型中的表达及作用机制[J]. 山东大学学报 (医学版), 2020, 1(7): 1 -6 .
[2] 马青源,蒲沛东,韩飞,王超,朱洲均,王维山,史晨辉. miR-27b-3p调控SMAD1对骨肉瘤细胞增殖、迁移和侵袭作用的影响[J]. 山东大学学报 (医学版), 2020, 1(7): 32 -37 .
[3] 张宝文,雷香丽,李瑾娜,罗湘俊,邹容. miR-21-5p靶向调控TIMP3抑制2型糖尿病肾病小鼠肾脏系膜细胞增殖及细胞外基质堆积[J]. 山东大学学报 (医学版), 2020, 1(7): 7 -14 .
[4] 付洁琦,张曼,张晓璐,李卉,陈红. Toll样受体4抑制过氧化物酶体增殖物激活受体γ加重血脂蓄积的分子机制[J]. 山东大学学报 (医学版), 2020, 1(7): 24 -31 .
[5] 龙婷婷,谢明,周璐,朱俊德. Noggin蛋白对小鼠脑缺血再灌注损伤后学习和记忆能力与齿状回结构的影响[J]. 山东大学学报 (医学版), 2020, 1(7): 15 -23 .
[6] 李宁,李娟,谢艳,李培龙,王允山,杜鲁涛,王传新. 长链非编码RNA AL109955.1在80例结直肠癌组织中的表达及对细胞增殖与迁移侵袭的影响[J]. 山东大学学报 (医学版), 2020, 1(7): 38 -46 .
[7] 徐玉香,刘煜东,张蓬,段瑞生. 101例脑小血管病患者脑微出血危险因素的回顾性分析[J]. 山东大学学报 (医学版), 2020, 1(7): 67 -71 .
[8] 丁祥云,于清梅,张文芳,庄园,郝晶. 胰岛素样生长因子II在84例多囊卵巢综合征患者颗粒细胞中的表达和促排卵结局的相关性[J]. 山东大学学报 (医学版), 2020, 1(7): 60 -66 .
[9] 肖娟,肖强,丛伟,李婷,丁守銮,张媛,邵纯纯,吴梅,刘佳宁,贾红英. 两种甲状腺超声数据报告系统诊断效能的比较[J]. 山东大学学报 (医学版), 2020, 1(7): 53 -59 .
[10] 史爽,李娟,米琦,王允山,杜鲁涛,王传新. 胃癌miRNAs预后风险评分模型的构建与应用[J]. 山东大学学报 (医学版), 2020, 1(7): 47 -52 .
版权所有 © 2018 《山东大学学报(医学版)》编辑部　
地址:山东大学科技期刊社（济南市历城区山大南路27号山东大学中心校区明德楼B座721室） 电话: 0531-88366918 E-mail: xbyxb@sdu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发