Article(id=1241102738025664642, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202404200, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1712851200000, receivedDateStr=2024-04-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773831551318, onlineDateStr=2026-03-18, pubDate=1721836800000, pubDateStr=2024-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773831551318, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773831551318, creator=13701087609, updateTime=1773831551318, updator=13701087609, issue=Issue{id=1241102730337505325, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='14', pageStart='2497', pageEnd='2688', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773831549486, creator=13701087609, updateTime=1773831697291, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241103350322745680, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241103350322745681, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102730337505325, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2497, endPage=2500, ext={EN=ArticleExt(id=1241102740491915463, articleId=1241102738025664642, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Incidence trends and age-period-cohort analyses of hepatitis C in China, 2006-2020, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the incidence trend of viral hepatitis C (HCV) in China from 2006 to 2020, and to explore the influence of age, period and birth cohort on the incidence of HCV.

Methods

The data of hepatitis C cases and demographic data were collected in China from 2006 to 2020. The Joinpoint regression model was applied to analyze the trend of the incidence of hepatitis C in the whole population and by age group. The age-period-cohort model was applied to explore the effects of age, period and birth cohort on the incidence.

Results

The incidence of hepatitis C increased from 2006 to 2020, and the average incidence was 12.82 per 100 000. Unlike other age groups, the incidence of hepatitis C in people age group 60 and above still showed an upward trend from 2010 to 2018 (APC=3.40). The time of onset effect of hepatitis C increased from 0.63 (95%CI: 0.77-0.70) during 2006-2010 to 0.92 (95%CI: 0.84-1.00) during 2016 to 2020. The birth cohort effect was lowest in the 1926-1930 cohort and peaked in the 1991-1995 cohort (RR=1.41, 95%CI: 1.01-1.97).

Conclusion

The incidence of hepatitis C increased during the study period, and the disease burden increased with age. High-risk groups should be regularly screened and monitored.

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目的

分析2006—2020年间中国丙型病毒性肝炎(丙肝)发病趋势,探索年龄、时期、出生队列对丙肝发病率产生的影响。

方法

收集2006—2020年间中国丙肝病例数据和人口学资料。应用Joinpoint回归模型分析全人群及分年龄组人群丙肝发病率的变化趋势,应用年龄-时期-队列模型探讨年龄、时期和出生队列对发病率的影响。

结果

2006—2020年间丙肝发病率整体呈现上升趋势,平均发病率为12.82/10万。与其他年龄组不同的是,60岁及以上年龄组人群丙肝发病在2010—2018年间仍呈现上升趋势(APC=3.40)。丙肝发病时期效应从2006—2010年期间的0.63(95%CI:0.57~0.70)升至2016—2020年间的0.92(95%CI:0.84~1.00);出生队列效应以1926—1930年出生人群最低,1991—1995年间出生的人群中达到峰值(RR=1.41,95%CI:1.01~1.97)。

结论

丙肝研究期间内发病率整体呈现上升趋势,疾病负担随年龄增长而增加。对于高危人群应当进行定期筛查,加强监测。

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张文义,E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点,除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=eHZ5ZlCD/py3iTOZXKFSwA==, magXml=/8ar4jvhm65XJUxmlZSdUQ==, pdfUrl=null, pdf=zw6/SLickC/OQSuZkwBsog==, pdfFileSize=1081080, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=kib71/EwmmCFVvMDhGpsMw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=NYhJQYn6di0ojuFGu1U9Pg==, mapNumber=null, authorCompany=null, fund=null, authors=

白峻竹(2000—),女,硕士在读,研究方向:公共卫生

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注:*代表P<0.05。

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2006—2020年中国丙型病毒性肝炎发病趋势及年龄-时期-队列分析
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白峻竹 1, 2 , 游姝萌 1, 2 , 张馨 1, 2 , 吕恒梁 1, 2 , 王勇 1, 2, 3 , 徐元勇 1, 2 , 张文义 1, 2, 3
现代预防医学 | 流行病与统计方法 2024,51(14): 2497-2500
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现代预防医学 | 流行病与统计方法 2024, 51(14): 2497-2500
2006—2020年中国丙型病毒性肝炎发病趋势及年龄-时期-队列分析
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白峻竹1, 2, 游姝萌1, 2, 张馨1, 2, 吕恒梁1, 2, 王勇1, 2, 3, 徐元勇1, 2, 张文义1, 2, 3
作者信息
  • 1.中国医科大学公共卫生学院,辽宁 沈阳 110000
  • 2.中国人民解放军疾病预防控制中心
  • 3.安徽医科大学公共卫生学院
  • 白峻竹(2000—),女,硕士在读,研究方向:公共卫生

通讯作者:

张文义,E-mail:
Incidence trends and age-period-cohort analyses of hepatitis C in China, 2006-2020
Jun-zhu BAI1, 2, Shu-meng YOU1, 2, Xin ZHANG1, 2, Heng-liang LV1, 2, Yong WANG1, 2, 3, Yuan-yong XU1, 2, Wen-yi ZHANG1, 2, 3
Affiliations
  • School of Public Health, China Medical University, Shenyang,Liaoning 110000, China
出版时间: 2024-07-25 doi: 10.20043/j.cnki.MPM.202404200
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目的

分析2006—2020年间中国丙型病毒性肝炎(丙肝)发病趋势,探索年龄、时期、出生队列对丙肝发病率产生的影响。

方法

收集2006—2020年间中国丙肝病例数据和人口学资料。应用Joinpoint回归模型分析全人群及分年龄组人群丙肝发病率的变化趋势,应用年龄-时期-队列模型探讨年龄、时期和出生队列对发病率的影响。

结果

2006—2020年间丙肝发病率整体呈现上升趋势,平均发病率为12.82/10万。与其他年龄组不同的是,60岁及以上年龄组人群丙肝发病在2010—2018年间仍呈现上升趋势(APC=3.40)。丙肝发病时期效应从2006—2010年期间的0.63(95%CI:0.57~0.70)升至2016—2020年间的0.92(95%CI:0.84~1.00);出生队列效应以1926—1930年出生人群最低,1991—1995年间出生的人群中达到峰值(RR=1.41,95%CI:1.01~1.97)。

结论

丙肝研究期间内发病率整体呈现上升趋势,疾病负担随年龄增长而增加。对于高危人群应当进行定期筛查,加强监测。

丙型病毒性肝炎  /  发病率  /  Joinpoint回归模型  /  年龄-时期-队列模型
Objective

To analyze the incidence trend of viral hepatitis C (HCV) in China from 2006 to 2020, and to explore the influence of age, period and birth cohort on the incidence of HCV.

Methods

The data of hepatitis C cases and demographic data were collected in China from 2006 to 2020. The Joinpoint regression model was applied to analyze the trend of the incidence of hepatitis C in the whole population and by age group. The age-period-cohort model was applied to explore the effects of age, period and birth cohort on the incidence.

Results

The incidence of hepatitis C increased from 2006 to 2020, and the average incidence was 12.82 per 100 000. Unlike other age groups, the incidence of hepatitis C in people age group 60 and above still showed an upward trend from 2010 to 2018 (APC=3.40). The time of onset effect of hepatitis C increased from 0.63 (95%CI: 0.77-0.70) during 2006-2010 to 0.92 (95%CI: 0.84-1.00) during 2016 to 2020. The birth cohort effect was lowest in the 1926-1930 cohort and peaked in the 1991-1995 cohort (RR=1.41, 95%CI: 1.01-1.97).

Conclusion

The incidence of hepatitis C increased during the study period, and the disease burden increased with age. High-risk groups should be regularly screened and monitored.

Hepatitis C  /  Incidence rate  /  Joinpoint regression model  /  Age-period-cohort model
白峻竹, 游姝萌, 张馨, 吕恒梁, 王勇, 徐元勇, 张文义. 2006—2020年中国丙型病毒性肝炎发病趋势及年龄-时期-队列分析. 现代预防医学, 2024 , 51 (14) : 2497 -2500 . DOI: 10.20043/j.cnki.MPM.202404200
Jun-zhu BAI, Shu-meng YOU, Xin ZHANG, Heng-liang LV, Yong WANG, Yuan-yong XU, Wen-yi ZHANG. Incidence trends and age-period-cohort analyses of hepatitis C in China, 2006-2020[J]. Modern Preventive Medicine, 2024 , 51 (14) : 2497 -2500 . DOI: 10.20043/j.cnki.MPM.202404200
丙型病毒性肝炎(简称丙肝)是由丙肝病毒(hepatitis c virus,HCV)感染所引起的以肝脏病变为主的传染性疾病,其传播方式为血液传播、性传播和母婴传播。截至2019年,全球每年约29万人死于丙肝,主要归因于肝硬化和肝癌[1]。中国是世界上丙型肝炎感染人数最多的国家之一[2],感染人数约760万,近年来年均报告病例达20万例[3]。目前我国尚无对于丙肝发病情况长期变化趋势的研究。本研究通过分析2006—2020年中国丙肝流行情况,探讨年龄、时期和出生队列效应对丙肝发病趋势的影响,为丙肝的科学防治提供依据。
2006—2020年中国丙肝发病数据来源于中国疾病预防控制中心公共卫生科学数据中 心,同期人口来源于国家统计局 2007—2021 年中国统计年鉴。
Joinpoint模型主要原理是将研究时期依据拐点分为不同区间,进行总体与分段的回归分析,对各区间进行统计分析。具体方法为以年为自变量、以疾病报告病例数或发病率为因变量的Joinpoint回归分析并依据修正贝叶斯信息准则进行最优模型拟合[4]。求得年度变化百分比(annual percentage changes,APC)、年均变化百分比(average annual percent change,AAPC)及95%置信区间(confidence interval,CI)。APC大于0表示发病呈现上升趋势,小于0则表示呈下降趋势。检验水准α=0.05[5]
该模型被广泛应用于探索年龄、时期和队列三者对于疾病发病情况的影响,分析疾病随时间发展的变化趋势。由于生命中的不同年龄阶段身体素质的差异,不同人群在不同时期内伴随不同的医疗和社会政策,以及不同出生队列间暴露环境不同会导致疾病发病情况的差异[6]。考虑到无法明确84岁年龄以上人群对应的出生队列,因此将研究的年龄定为0~84岁,将年龄按照五岁分成一组,共得到17个年龄组。依据年龄-时期-队列模型要求,统一年龄及时期时间间隔,按五年一组,将2006—2020年数据分为3组;1926—2020年出生年份分为19个队列进行综合分析。选取各自间隔内的中位时期和队列定义为对照组,参考时期选取2011—2015年,参考队列选取1971—1975年。年龄曲线表明调整时期、队列后的按年龄发病率,时期(队列)率比(rate ratio,RR)表示与对照组相比的时期(队列)效应的相对风险[7]。参数估计应用Wald χ2检验,检验水准α=0.05。
应用Excel 2019软件对数据进行统计分析,应用Joinpoint regression program(JRP)4.9.1.0软件建立模型并计算APC,AAPC以及95%CI值。年龄时期队列模型采用美国国立卫生研究院的分析工具(https://analysistools.nci.nih.gov/apc/),同时应用R 4.2.3及Origin 2021软件进行结果整理和绘图。
2006—2020年,丙肝累计发病人数为2 603 698例,平均发病率为12.82/10万,发病率呈上升趋势,其中2019年发病数和发病率最高,达223 660例(16.02/10万),见图1
2006—2020年,丙肝发病在2006—2012年间呈现上升趋势(APC=17.69%,P<0.05),2012—2020年间变化不具有统计学意义(APC=-0.31%, P=0.67)。分年龄的回归分析表明,2006—2020年间,除20~39岁人群丙肝发病变化没有统计学意义以外,其余年龄段的发病率变化在2006—2012年间均呈现上升趋势。APC在0~19岁,40~59岁,60岁及以上人群中分别为11.42%,20.34%及20.03%。除60岁及以上人群丙肝发病在2010—2018年间APC为3.4%,其余各年龄组人群变化不明显(P>0.05),见图2
2006—2020年间,中国全人群丙肝发病率的全局变化、总年龄偏差、总队列偏差及APC系数均有统计学意义(P<0.05),疾病发病具有年龄-时期-队列效应。调整时期和队列后,丙肝发病率呈现随年龄增长而上升的趋势,从0~4岁时的2.91/10万升至80~84岁时的515.81/10万,见图3A
调整年龄和队列后,2006—2020年丙肝发病率的时期效应RR值呈现先上升后下降的趋势,以2011—2015年为参考时期(RR=1),2006—2010年期间丙肝RR值为0.63(95%CI:0.57~0.70),为研究阶段内最低水平,2016—2020年时期效应RR值下降,为0.92(95%CI:0.84~1.00),见图3B
调整年龄、时期后,以1971—1975年间出生的人群为参考队列(RR=1),1976—1995年丙肝发病的队列效应RR值均大于1。1926—1930年出生人群的队列效应RR值最低,为0.05(95%CI:0.02~0.09),队列效应RR值随后逐渐上升,在1991—1995年间出生的人群中达到峰值,为1.41(95%CI:1.01~1.97)。1996年及以后出生的人群队列效应RR值下降幅度明显,2001—2005 年出生人群队列效应RR呈上升趋势,2006年及以后出生人群队列效应RR值再次下降。图3C
Joinpoint回归分析显示,0~19岁,40~59岁人群发病在2006—2012年间上升趋势明显,2012年后发病较为平稳,与总人群发病变化趋势相同,仅60岁及以上人群发病在2010—2018年间仍然呈现上升趋势。丙肝增长速度的减缓可能与近年来人群卫生意识提高,医疗条件改善和2019年更新的《丙型肝炎防治指南》加强了丙肝诊断和防治的规范性[8]有关。然而,2016年中国只有18%的丙肝患者得到诊断,大量患者未及时治疗并继续传播疾病,这导致丙肝发病没有明显下降趋势[9-10]
年龄效应显示,丙肝的调整发病率呈现随年龄增长而上升的趋势,以50岁为转折点出现明显上升趋势。此类情况可能是由于丙型肝炎具有隐匿性、潜伏期长等特征以及病毒持续感染所造成的累积效应[11]。同时,我国早期医疗条件较差,年长者既往具有不洁输血输液、非法采血等治疗暴露风险高[12],且高年龄人群自身基础疾病较多,就医的机会多,具有更高的丙肝检出概率。中国老龄化的持续加剧可能会使丙肝的防控工作在未来面对更大的挑战,这也提示我们,对于高年龄且具有既往不洁医疗史的高危人群,应当加强检测和筛查,做好预防和治疗工作。
时期效应显示,2006—2010年丙肝的发病上升较为明显,2016—2020年发病风险下降缓慢。2004年丙肝网络直报的实行,病毒抗体检测试剂的普及和医疗条件的提高是2006—2010年疾病发病风险增加的可能原因[13]。2017年中国发布《中国病毒性肝炎防治规划(2017—2020年)》,从防治措施、医疗保障等方面加强了对肝炎防治的全面性[8],2018年卫生部颁布修订的WS 213—2008丙肝诊断标准[14],这一标准对HCV RNA阴性者进行订正、删除,提升了疾病的报告质量,一定程度降低了病例的增长。另外,直接抗病毒药物(direct-acting antiviral agents, DAAs)2017年引入我国,在丙肝治疗中持续病毒学应答达95%,极大地提高了丙肝治疗的有效率[15]。然而,由于其治疗成本较高,引入后未能得到普及。2019年部分DAAs药物纳入医保,这一举措可能在未来治愈更多的丙肝患者[16]
出生队列效应显示,研究期间内,1991—1995年间出生人群丙肝发病风险达最高水平,1996年及以后出生人群发病风险下降,可能的原因为1992年后加强血液管理,对献血人员HCV感染情况进行强制筛查,降低疾病的传播[13]。值得注意的是,2001年及以后出生人群发病风险有小幅度上升,这可能与近年来中国丙肝感染的原因改变有关。20世纪初,注射吸毒者共用注射器致交叉感染、高危性行为、多个性伴侣及使用黏膜给药的娱乐性药物等成为丙肝感染风险增加的重要危险因素[17-19]。此外,侵入性美容行业在年轻人群中的盛行也可能是丙肝发病风险提高的原因之一[20]
综上所述,2006—2020年间丙肝发病率整体呈现上升趋势,老年人是丙肝发病的高危人群。《2030年可持续发展议程》提出,到2030年,病毒性肝炎感染率降低90%,血液制品筛查率达到100%[21]。为实现这一目标,公共卫生部门应完善疾病信息报告系统,加强血液管理;对于高危人群如年长者、有不洁医疗史者等进行定期筛查和监测,早期发现疾病并及时采取抗病毒药物治疗。同时进行医疗宣讲及健康宣教,提高群众对丙肝知识的了解。
  • 国家科技重大专项(2018ZX10713003)
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2024年第51卷第14期
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doi: 10.20043/j.cnki.MPM.202404200
  • 接收时间:2024-04-12
  • 首发时间:2026-03-18
  • 出版时间:2024-07-25
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  • 收稿日期:2024-04-12
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国家科技重大专项(2018ZX10713003)
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    1.中国医科大学公共卫生学院,辽宁 沈阳 110000
    2.中国人民解放军疾病预防控制中心
    3.安徽医科大学公共卫生学院

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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