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Article(id=1321170066515808401, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1321169992024961657, articleNumber=null, orderNo=null, doi=10.11847/zgggws1145773, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1730304000000, receivedDateStr=2024-10-31, revisedDate=1737302400000, revisedDateStr=2025-01-20, acceptedDate=1741881600000, acceptedDateStr=2025-03-14, onlineDate=1792921090009, onlineDateStr=2026-10-25, pubDate=1744214400000, pubDateStr=2025-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792921090009, onlineIssueDateStr=2026-10-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792921090009, creator=13701087609, updateTime=1792921090009, updator=13701087609, issue=Issue{id=1321169992024961657, tenantId=1146029695717560320, journalId=1319373219989389464, year='2025', volume='41', issue='4', pageStart='385', pageEnd='512', issueExtLink='null', onlineDate='null', pubDate='1744214400000', pubDateStr='2025-04-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792921072250, creator='13701087609', updateTime=1792921072250, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=477, endPage=482, ext={EN=ArticleExt(id=1321170066733912210, articleId=1321170066515808401, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Age-period-cohort analysis of early syphilis in Shandong province from 2006 to 2020, columnId=1320427686514770171, journalTitle=Chinese Journal of Public Health, columnName=Survey and Report, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the incidence and trends of early syphilis in Shandong province and provide references for syphilis prevention and control.

Methods

Data for this study were obtained from the China Public Health Science Data Center. Joinpoint regression was used to analyze trends in incidence rates, and age-period-cohort (APC) models were used to analyze the effects of age, period, and birth cohort.

Results

From 2006 to 2020, the incidence of early syphilis in Shandong province initially increased and then decreased. The average annual percentage change (AAPC) for primary and secondary syphilis was 6.02% and 6.25%, respectively. The proportion of cases in the 0–19 and ≥60 age groups has been increasing. Age-period-cohort analysis showed that the 20–24 age group had the highest incidence of early syphilis, with incidence rates of 10.47/100 000 and 16.67/100 000 for primary and secondary syphilis, respectively. The risk of disease first increased and then decreased over time. With the progression of birth cohorts, the risk of disease continued to increase, peaking in 2006–2010, with relative risks (RR) of 6.38 and 8.58 for primary and secondary syphilis, respectively.

Conclusions

The incidence of early syphilis in Shandong province showed a trend of first increasing and then decreasing. The 20–24 age group had the highest risk of disease, and the proportion of cases in the 0–19 and ≥60 age groups has been increasing.

, authors=Zhenghao WU, Yu DONG, Xinyu CAI, Fengyue ZHANG, Hongqing LIU, authorsList=Zhenghao WU, Yu DONG, Xinyu CAI, Fengyue ZHANG, Hongqing LIU, authorCompany=null, correspAuthors=Hongqing LIU, authorNote=null, correspAuthorsNote=
LIU Hongqing, E-mail:
, copyrightStatement=Copyright © 2025 Chinese Journal of Public Health. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1321170067719573659, articleId=1321170066515808401, tenantId=1146029695717560320, journalId=1319373219989389464, language=CN, title=2006—2020年山东省早期梅毒年龄–时期–队列分析, columnId=1320427686770622717, journalTitle=中国公共卫生, columnName=调查报告与分析, runingTitle=null, highlight=null, articleAbstract=
目的

探讨山东省早期梅毒的发病情况和变化趋势，为梅毒的防控提供参考。

方法

本研究数据来自中国公共卫生科学数据中心，采用joinpoint回归模型分析发病率变化趋势、利用APC模型分析年龄、时期和出生队列的影响效应。

结果

2006—2020年山东省早期梅毒呈先上升后降低趋势，I期、II期梅毒的平均年度变化百分比分别为6.02%、6.25%；0～19岁和≥60岁年龄段发病人数占比在不断增加。年龄–时期–队列分析显示，20～24岁年龄组为早期梅毒的发病高峰，I期、II期梅毒发病率分别为10.47/10万和16.67/10万；随时期的推移发病风险先升高后降低；随着出生队列的不断推移发病风险不断升高，在2006—2010年达到峰值，I期、II期梅毒RR值分别为6.38和8.58。

结论

山东省早期梅毒呈先上升后降低趋势，20～24岁年龄组发病风险最高，0～19岁和≥60岁年龄段发病人数占比在不断增加。

, authors=吴正昊, 董宇, 蔡新宇, 张凤悦, 刘洪庆*, *, authorsList=吴正昊, 董宇, 蔡新宇, 张凤悦, 刘洪庆, authorCompany=null, correspAuthors=刘洪庆, authorNote=

吴正昊（2001—），硕士在读，研究方向：流行病与卫生统计学

, correspAuthorsNote=
刘洪庆，E-mail：
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吴正昊（2001—），硕士在读，研究方向：流行病与卫生统计学

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吴正昊（2001—），硕士在读，研究方向：流行病与卫生统计学

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注：图中实线与2条虚线分别为净漂移值及95%置信区间。

, figureFileSmall=j/Axpvl20CoQmWis9Sfplw==, figureFileBig=MyaTHVLVxS9FbtMdTNkrEg==, tableContent=null), ArticleFig(id=1321170071821603011, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=EN, label=Fig.2, caption=Age-specific incidence rates of early syphilis in Shandong province from 2006 to 2020, figureFileSmall=SSfxLsctqgowL07dRLFY5A==, figureFileBig=D0+KP6pSj2JbsjToHvIEMw==, tableContent=null), ArticleFig(id=1321170071897100484, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=CN, label=图2, caption=2006—2020年山东省早期梅毒发病率的年龄效应, figureFileSmall=SSfxLsctqgowL07dRLFY5A==, figureFileBig=D0+KP6pSj2JbsjToHvIEMw==, tableContent=null), ArticleFig(id=1321170071968403653, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=EN, label=Fig.3, caption=Period effect of early syphilis incidence in Shandong province from 2006 to 2020, figureFileSmall=aJfb3L76fnruBBx0FSjdwA==, figureFileBig=ATO4JgUI5p9nRmekoUQWKQ==, tableContent=null), ArticleFig(id=1321170072052289734, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=CN, label=图3, caption=2006—2020年山东省早期梅毒发病率的时期效应, figureFileSmall=aJfb3L76fnruBBx0FSjdwA==, figureFileBig=ATO4JgUI5p9nRmekoUQWKQ==, tableContent=null), ArticleFig(id=1321170072136175815, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=EN, label=Fig.4, caption=Cohort effect of early syphilis incidence in Shandong province from 2006 to 2020, figureFileSmall=DsHaAJCZ0lztzvxfNFxrZg==, figureFileBig=m2QB2PX+21yeVgdB0cYhRw==, tableContent=null), ArticleFig(id=1321170072241033416, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=CN, label=图4, caption=2006—2020年山东省早期梅毒发病率的队列效应, figureFileSmall=DsHaAJCZ0lztzvxfNFxrZg==, figureFileBig=m2QB2PX+21yeVgdB0cYhRw==, tableContent=null), ArticleFig(id=1321170072329113801, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=EN, label=Tab.1, caption=

Reported cases and incidence of early syphilis in Shandong province, 2006–2020

, figureFileSmall=null, figureFileBig=null, tableContent=
年份Ⅰ期梅毒Ⅱ期梅毒
发病数/例发病率/（1/10万）发病数/例发病率/（1/10万）
20067830.788600.85
20079360.939780.97
20081 2031.191 4771.47
20091 6651.652 0412.03
20101 8961.882 3512.33
20112 1892.172 5842.57
20122 5702.5534333.41
20133 2013.1734843.46
201435633.533 3293.31
20153 3323.312 9192.90
20162 9842.962 8212.80
201730243.002 8592.84
20182 5952.582 7572.74
20192 4742.462 4902.47
20201 9791.972 0122.00
), ArticleFig(id=1321170072408805578, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=CN, label=表1, caption=

2006—2020年山东省早期梅毒报告发病例数与发病率

, figureFileSmall=null, figureFileBig=null, tableContent=
年份Ⅰ期梅毒Ⅱ期梅毒
发病数/例发病率/（1/10万）发病数/例发病率/（1/10万）
20067830.788600.85
20079360.939780.97
20081 2031.191 4771.47
20091 6651.652 0412.03
20101 8961.882 3512.33
20112 1892.172 5842.57
20122 5702.5534333.41
20133 2013.1734843.46
201435633.533 3293.31
20153 3323.312 9192.90
20162 9842.962 8212.80
201730243.002 8592.84
20182 5952.582 7572.74
20192 4742.462 4902.47
20201 9791.972 0122.00
), ArticleFig(id=1321170072496885963, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=EN, label=Tab.2, caption=

Number and proportion of early syphilis cases in different age groups in Shandong province from 2006 to 2020

, figureFileSmall=null, figureFileBig=null, tableContent=
年份I期梅毒II期梅毒
0～19岁20～59岁≥60岁0～19岁20～59岁≥60岁
病例数/例占比/%病例数/例占比/%病例数/例占比/%病例数/例占比/%病例数/例占比/%病例数/例占比/%
2006212.6868787.74759.58354.0776989.42566.51
2007323.4278683.9711812.61282.8688990.90616.24
2008615.071 03886.281048.65755.081 34190.79614.13
2009704.201 46187.751348.05864.211 87491.82813.97
2010603.161 67088.081668.76974.132 15491.621004.25
2011773.521 89986.752139.731375.302 31589.591325.11
2012893.462 21085.9927110.541725.013 04888.792136.20
20131183.692 70384.4438011.871945.57301086.392808.04
20141233.452 95883.048213.531775.322 84285.373109.31
20151333.992 72581.7847414.232006.852 44283.662779.49
20161143.822 28476.5458619.641695.992 29981.5035312.51
20171133.742 23974.0467222.221976.892 25378.8040914.31
20181415.431 83870.8361623.741926.962 14977.9541615.09
20191405.661 71469.2862025.061897.591 95078.3135114.10
20201417.121 31966.6551926.231698.401 54876.9429514.66
χ2趋势38.82847.27811.6893.68667.88579.18
P值<0.05 <0.05 <0.05<0.05 <0.05 <0.05
), ArticleFig(id=1321170072597549260, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=CN, label=表2, caption=

2006—2020年山东省早期梅毒各年龄段发病例数及其占比

, figureFileSmall=null, figureFileBig=null, tableContent=
年份I期梅毒II期梅毒
0～19岁20～59岁≥60岁0～19岁20～59岁≥60岁
病例数/例占比/%病例数/例占比/%病例数/例占比/%病例数/例占比/%病例数/例占比/%病例数/例占比/%
2006212.6868787.74759.58354.0776989.42566.51
2007323.4278683.9711812.61282.8688990.90616.24
2008615.071 03886.281048.65755.081 34190.79614.13
2009704.201 46187.751348.05864.211 87491.82813.97
2010603.161 67088.081668.76974.132 15491.621004.25
2011773.521 89986.752139.731375.302 31589.591325.11
2012893.462 21085.9927110.541725.013 04888.792136.20
20131183.692 70384.4438011.871945.57301086.392808.04
20141233.452 95883.048213.531775.322 84285.373109.31
20151333.992 72581.7847414.232006.852 44283.662779.49
20161143.822 28476.5458619.641695.992 29981.5035312.51
20171133.742 23974.0467222.221976.892 25378.8040914.31
20181415.431 83870.8361623.741926.962 14977.9541615.09
20191405.661 71469.2862025.061897.591 95078.3135114.10
20201417.121 31966.6551926.231698.401 54876.9429514.66
χ2趋势38.82847.27811.6893.68667.88579.18
P值<0.05 <0.05 <0.05<0.05 <0.05 <0.05
), ArticleFig(id=1321170072694018253, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=EN, label=Tab.3, caption=

Joinpoint regression analysis of the incidence trend of early syphilis in Shandong province from 2006 to 2020

, figureFileSmall=null, figureFileBig=null, tableContent=
类型时间段APC/%95%CIAAPC/%95%CIt值P值
Ⅰ期梅毒2006—201419.3316.50～22.2316.39<0.05
2014—2020–9.38–11.95～–6.74–7.63<0.05
2006—20206.054.35～7.797.10<0.05
Ⅱ期梅毒2006—201225.1018.52～32.059.23<0.05
2012—2020–6.00–8.37～–3.58–5.42<0.05
2006—20206.253.72～8.834.94<0.05
), ArticleFig(id=1321170072811458766, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1321170066515808401, language=CN, label=表3, caption=

2006—2020年山东省早期梅毒发病率趋势的Joinpoint回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
类型时间段APC/%95%CIAAPC/%95%CIt值P值
Ⅰ期梅毒2006—201419.3316.50～22.2316.39<0.05
2014—2020–9.38–11.95～–6.74–7.63<0.05
2006—20206.054.35～7.797.10<0.05
Ⅱ期梅毒2006—201225.1018.52～32.059.23<0.05
2012—2020–6.00–8.37～–3.58–5.42<0.05
2006—20206.253.72～8.834.94<0.05
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2006—2020年山东省早期梅毒年龄–时期–队列分析
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吴正昊 , 董宇 , 蔡新宇 , 张凤悦 , 刘洪庆 *, *
中国公共卫生 | 调查报告与分析 2025,41(4): 477-482
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中国公共卫生 |调查报告与分析 2025 , 41 (4) : 477 -482
2006—2020年山东省早期梅毒年龄–时期–队列分析
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吴正昊（2001—），硕士在读，研究方向：流行病与卫生统计学

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吴正昊, 董宇, 蔡新宇, 张凤悦, 刘洪庆*, *
作者信息
  • 山东第二医科大学公共卫生学院，山东 潍坊 261053
通讯作者:
刘洪庆，E-mail：
作者简介:

吴正昊（2001—），硕士在读，研究方向：流行病与卫生统计学

Age-period-cohort analysis of early syphilis in Shandong province from 2006 to 2020
Zhenghao WU, Yu DONG, Xinyu CAI, Fengyue ZHANG, Hongqing LIU
Affiliations
  • School of Public Health, Shandong Second Medical University, Weifang 261053, Shandong, China
    • Corresponding Author:
    LIU Hongqing, E-mail:
出版时间: 2025-04-10 doi: 10.11847/zgggws1145773
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摘要
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目的

探讨山东省早期梅毒的发病情况和变化趋势，为梅毒的防控提供参考。

方法

本研究数据来自中国公共卫生科学数据中心，采用joinpoint回归模型分析发病率变化趋势、利用APC模型分析年龄、时期和出生队列的影响效应。

结果

2006—2020年山东省早期梅毒呈先上升后降低趋势，I期、II期梅毒的平均年度变化百分比分别为6.02%、6.25%；0～19岁和≥60岁年龄段发病人数占比在不断增加。年龄–时期–队列分析显示，20～24岁年龄组为早期梅毒的发病高峰，I期、II期梅毒发病率分别为10.47/10万和16.67/10万；随时期的推移发病风险先升高后降低；随着出生队列的不断推移发病风险不断升高，在2006—2010年达到峰值，I期、II期梅毒RR值分别为6.38和8.58。

结论

山东省早期梅毒呈先上升后降低趋势，20～24岁年龄组发病风险最高，0～19岁和≥60岁年龄段发病人数占比在不断增加。

梅毒  /  joinpoint回归模型  /  年龄–时期–队列模型  /  山东省
Objective

To investigate the incidence and trends of early syphilis in Shandong province and provide references for syphilis prevention and control.

Methods

Data for this study were obtained from the China Public Health Science Data Center. Joinpoint regression was used to analyze trends in incidence rates, and age-period-cohort (APC) models were used to analyze the effects of age, period, and birth cohort.

Results

From 2006 to 2020, the incidence of early syphilis in Shandong province initially increased and then decreased. The average annual percentage change (AAPC) for primary and secondary syphilis was 6.02% and 6.25%, respectively. The proportion of cases in the 0–19 and ≥60 age groups has been increasing. Age-period-cohort analysis showed that the 20–24 age group had the highest incidence of early syphilis, with incidence rates of 10.47/100 000 and 16.67/100 000 for primary and secondary syphilis, respectively. The risk of disease first increased and then decreased over time. With the progression of birth cohorts, the risk of disease continued to increase, peaking in 2006–2010, with relative risks (RR) of 6.38 and 8.58 for primary and secondary syphilis, respectively.

Conclusions

The incidence of early syphilis in Shandong province showed a trend of first increasing and then decreasing. The 20–24 age group had the highest risk of disease, and the proportion of cases in the 0–19 and ≥60 age groups has been increasing.

syphilis  /  Joinpoint regression model  /  age-period-cohort (APC) model  /  Shandong province
吴正昊, 董宇, 蔡新宇, 张凤悦, 刘洪庆. 2006—2020年山东省早期梅毒年龄–时期–队列分析. 中国公共卫生, 2025 , 41 (4) : 477 -482 . DOI: 10.11847/zgggws1145773
Zhenghao WU, Yu DONG, Xinyu CAI, Fengyue ZHANG, Hongqing LIU. Age-period-cohort analysis of early syphilis in Shandong province from 2006 to 2020[J]. Chinese Journal of Public Health, 2025 , 41 (4) : 477 -482 . DOI: 10.11847/zgggws1145773
正文
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梅毒 （syphilis） 是由梅毒螺旋体或称苍白螺旋体（Treponema pallidum，TP） 引起的一种性传播和垂直传播疾病，其临床表现极为复杂，几乎侵犯全身各器官，造成多器官的损害，并且可以通过垂直传播导致孕妇出现流产、死胎、早产、先天梅毒等不良妊娠结局[1–2]。依据梅毒诊断标准，梅毒可分为I期梅毒、II期梅毒、III期梅毒、胎传梅毒和隐性梅毒，根据病程I期梅毒与II期梅毒被分为早期梅毒[3]，通过规范治疗早期梅毒可被较好地治愈[4]，并且可以反映成年人梅毒新近感染状况[5]。为探究山东省早期梅毒发病率的变化趋势和影响因素，本研究对2006—2020年山东省早期梅毒发病率变化趋势和早期梅毒的年龄、时期与出生队列的影响效应进行分析，旨在为山东省早期梅毒的防控和治疗提供理论依据。
1　数据与方法
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1.1　数据来源
本研究通过中国疾病预防控制中心的公共卫生科学数据平台收集2006—2020年山东省早期梅毒的各年龄组发病数据，采用第七次人口普查数据作为人口学资料。
1.2　方法
1.2.1　Joinpoint回归模型[6]
Joinpoint 回归模型利用网格搜索法（grid search method，GSM）确定所有可存在的各段区间的函数连接点，然后同时计算各点相对应的均方误差之和（sum of squares errors，SSE）和均方差（mean squared errors，MSE）。通过对比获得的可能点，选择 MSE、SSE 最小的点定为区间分段函数连接点，并以此准备的连接点与区间参数拟合方程函数，从而获得模型函数方程。模型的优化利用了Monte Carlo置换检验（permutation test）[7]，该模型用年度变化百分比（annual percent of changes，APC）和完整时间区间内平均年度变化百分比（average annual percent change，AAPC）来描述变化趋势。当APC值<0时，说明发病率在该时段内逐渐下降；若APC值>0，则表示发病率在该时段内呈上升趋势。
1.2.2　APC模型
年龄–时期–队列模型（age-period-cohort-model，简称APC模型）可以解释人口数据中的变化和趋势，并识别出年龄效应、时期效应和队列效应对其变化的影响。年龄效应是指不同年龄段的个体在心理、行为、健康等方面可能表现出的差异，而造成发病风险差异；时期效应是指研究的特定时间点或年份，反映宏观社会、经济和文化环境的变化对所有年龄段个体的普遍效应；队列效应是指早年生活条件或社会经历对在同一年份（时段）出生的人产生的影响。将0～74岁居民纳入APC模型，并将其分为15个年龄组（0～4、5～9、……、70～74岁），将2006—2020年分为3个时期组（2006—2010、2011—2015、2016—2020年），相应的出生队列分为17组（1936—1940、1941—1945、……、2016—2020年）。
1.3　统计分析
采用Excel 2020对I期、II期梅毒数据进行整理，建立数据库，将总发病例数按照年龄分为0～19、20～59和≥60岁3个年龄段，使用SPPS27.0对3个年龄段发病例数构成比进行趋势χ2检验，使用Joinpoint4.0.1分析山东省I期、II期梅毒的变化趋势；使用NCI提供的在线工具（https://analysistools.cancer.gov/apc/）对山东省I期、II期梅毒进行APC分析，检验水准α=0.05。
2　结　果
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2.1　早期梅毒发病情况（表1）
山东省I期梅毒发病例数由2006年783例增长到2020年的1 979例，发病率由2006年0.78/10万上升至2014年3.53/10万，呈上升趋势，随后发病率呈现下降趋势；II期梅毒发病例数由2006年860例增长到2020年的2 012例，发病率由2006年0.85/10万上升至2013年3.46/10万，呈上升趋势，随后发病率呈现下降趋势。
2.2　各年龄段发病例数占比（表2）
20～59岁年龄段I期、II期梅毒发病例数在各年中均占比最大；0～19岁年龄段I期、II期梅毒发病例数占比随时间推移不断升高，I期梅毒占比由2006年的2.68%增长到2020年的7.12%（χ2趋势=38.81，P<0.05），II期梅毒占比由2006年的4.07%增长到2020年的8.40%（χ2趋势=93.68，P<0.05）；≥60岁年龄段I期、II期梅毒发病例数占比同样随时间推移不断升高，I期梅毒占比由2006年的9.58%增长到2020年的26.2%（χ2趋势=811.68，P<0.05），II期梅毒占比由2006年的6.51%增长到2020年的14.66%（χ2趋势=579.18，P<0.05）。
2.3　joinpoint回归分析（表3）
I期梅毒的AAPC=6.05%（95%CI=4.35%～7.79%，P<0.05），在2014年出现转折点，2006—2014和2014—2020年的APC值分别为19.33%（95%CI=16.50%～22.23%，P<0.05）和–9.38%（95%CI= –11.95%～–6.74%，P<0.05），2006—2020年I期梅毒呈现先升高后降低的趋势；II期梅毒的AAPC=6.25%（95%CI=3.72%～8.83%，P<0.05），在2012年出现转折点，2006—2012和2012—2020年的APC值分别为25.10%（95%CI=18.52%～32.05%，P<0.05）和–6.00%（95%CI = –8.37%～–3.58%，P<0.05），2006—2020年II期梅毒呈现先升高后降低的趋势。
2.4　APC模型分析
2.4.1　净漂移值与局部漂移值（图1）
2006—2020年山东省I期、II期梅毒的净漂移值分别为8.23%（95%CI=5.51%～11.01%）、7.61%（95%CI=5.23%～10.17%），I期、II期梅毒局部漂移值随年龄增长总体均呈现双峰分布，次高峰均为10～14年龄组，局部漂移值分别为14.38%（95%CI= –10.59%～46.33%）、18.18%（95%CI= –4.03%～45.52%）；主高峰均为65～69岁年龄组，局部漂移值分别为21.80%（95%CI=16.36%～27.49%）、21.28%（95%CI=14.03%～28.98%）。
2.4.2　年龄效应（图2）
I期、II期梅毒0～4岁年龄组的发病率高于5～9岁和10～14岁年龄组，15～19岁年龄组开始发病率呈上升趋势，20～24岁年龄组发病率最高，发病率分别为10.47/10万和16.67/10万，随之呈下降趋势；I期、II期梅毒均在55～59岁年龄组后发病率随年龄增加而增长。
2.4.3　时期效应（图3）
将2011—2015年作为对照组（RR值=1），I期、II期梅毒在2006—2010年RR值分别在0.41和0.44增长到1，发病风险呈上升趋势；2016—2020年RR值分别降低为0.90和0.91，发病风险呈下降趋势。
2.4.4　队列效应（图4）
将1976—1980年出生队列作为对照组（RR值=1），随着出生队列的不断推移I期、II期梅毒的发病风险不断升高，1961—1965年出生队列开始发病风险增长速度加快，2006—2010年出生队列发病风险达到峰值，RR值分别为6.38和8.58，随后呈下降趋势。
3　讨　论
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研究结果显示，2006—2020年山东省早期梅毒的发病率呈现先上升后降低趋势，与湖南省的早期梅毒发病率的变化趋势相同[8]，发病率的升高有以下几方面的原因：首先，山东省流动人口呈增长趋势，由2010年1 133.64万人增加到2020年的2 074.33万人，位居全国第五位[9]，山东省流动人群以青壮年为主，该人群存在一定比例的非婚性行为、同性性行为等高危行为且安全套的使用率较低[10]，在流入地高危行为使梅毒在当地传播，返乡后导致梅毒在家庭成员间传播，为梅毒的传播起到了“桥梁”作用[11]；其次，商业性性行为、婚前和婚外性接触、男男性接触等高危行为日益多样化，导致感染梅毒的风险增加[12]；最后，随着《山东省预防与控制梅毒规划（2010—2020年）》的实施提高梅毒疫情报告的质量，减少重复报告、误报和漏报，同时开展主动检测，对有可疑梅毒临床表现者主动建议进行梅毒检测，增加了检出概率[13]。时期效应结果与joinpoint中转折时间节点的出现说明山东省早期梅毒在2010—2015年后得到了有效控制。证明2011年出台《山东省预防与控制梅毒规划（2010—2020年）》开展宣传梅毒教育，普及梅毒防治知识，开展综合干预，阻断梅毒传播，提供规范化梅毒医疗服务等措施取得了显著成效[13]。
各年龄段发病例数占比和净漂移值与局部漂移值结果显示，0～19岁年龄段占比不断增加且局部漂移值在10～14岁出现次高峰，其原因可能是初次发生性行为趋于低龄化[14]，该人群年龄较小缺乏自我安全意识和追求刺激而不使用安全套，导致感染梅毒的概率增加[15]；≥60岁年龄段占比不断增加且局部漂移值在65～69岁年龄组出现主高峰，其原因可能是居民生活水平不断提高，老年人的性需求也不断增加，但老年人文化程度较低使对梅毒宣传工作在该人群中的效果较差，导致对梅毒相关知识知晓率较低[16]；另一方面，由于老年人思想传统和隐私保护意识较强，导致安全套的使用率较低[17]；并且老年人较其他人群因其他疾病前往医院就诊的频率较高，导致其检出率升高。
年龄效应结果显示，早期梅毒中0～4岁年龄组的发病率高于5～9和10～14岁年龄组，古丽加衣娜·艾肯的研究也表明I期梅毒在0～4岁有低发病风险[18]，其原因可能是儿童梅毒病例多为先天梅毒即胎传梅毒，可能因为新生儿的梅毒筛查不足导致发展为I期梅毒或II期梅毒；其次由于卫生意识较差咀嚼食物喂养、亲吻等亲密的生活方式也会导致患病风险的增加[19]；20～24岁年龄组发病率最高，该年龄段处于性活跃时期，且性行为和生活方式较为开放，使不安全性行为和吸食毒品的发生概率增加[12,20]；早期梅毒自55～59岁年龄组开始发病率随年龄的增加而增长，其原因与≥60岁年龄段占比不断增加相同，且有研究表明随着年龄的增长梅毒老年患者的假阳性率也随之增加[21]。
队列效应结果显示，早期梅毒的发病风险随着出生队列不断升高，均在2006—2010年出生队列的发病风险达到最高。不同的出生队列的生存背景、社会发展状况、生活习惯、思维方式、受教育水平等因素不同，导致其发病风险出现差异。我国梅毒重新流行，发病率逐年增加[22]，致使较晚年龄队列的发病风险不断升高；2006—2010年出生队列发病风险较高，可能是因为随着网络的普及，同性性行为、多个性伴侣等高危行为发生率较高，思想尚未成熟缺乏判断能力对新鲜事物有较高的接受度，导致其婚恋价值观易受到的负面影响，增加了感染梅毒的风险[23]；2010年后的出生队列发病风险降低是因为卫生部门出台一系列梅毒防控政策及科普宣教，且该年龄段儿童尚未达到性成熟期。
综上所述，山东省早期梅毒发病率呈现先上升后降低趋势，2015年后得到有效控制；梅毒防控工作应着重注意青少年和老年人群，建议有针对性开展梅毒预防讲座，广泛宣传梅毒的危害、早期发现和规范诊疗的重要性；持续推广自愿咨询检测、医疗机构扩大筛检、社会组织动员检测、重点人群自我检测等多种途径；加强性病门诊就诊者的宣传教育和隐私保护，从而调动患者对后续治疗的积极性。

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2025年第41卷第4期
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doi: 10.11847/zgggws1145773
  • 接收时间：2024-10-31
  • 首发时间：2026-10-25
  • 出版时间：2025-04-10
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  • 收稿日期：2024-10-31
  • 修回日期：2025-01-20
  • 录用日期：2025-03-14
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    山东第二医科大学公共卫生学院，山东 潍坊 261053

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刘洪庆，E-mail：
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
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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