Article(id=1259565965453439741, tenantId=1146029695717560320, journalId=1259198908832956435, issueId=1259565961842123095, articleNumber=null, orderNo=null, doi=10.16462/j.cnki.zhjbkz.2026.02.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1755619200000, receivedDateStr=2025-08-20, revisedDate=1764691200000, revisedDateStr=2025-12-03, acceptedDate=null, acceptedDateStr=null, onlineDate=1778233527768, onlineDateStr=2026-05-08, pubDate=1770652800000, pubDateStr=2026-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1778233527768, onlineIssueDateStr=2026-05-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1778233527768, creator=13701087609, updateTime=1778233527768, updator=13701087609, issue=Issue{id=1259565961842123095, tenantId=1146029695717560320, journalId=1259198908832956435, year='2026', volume='30', issue='2', pageStart='125', pageEnd='242', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1778233526907, creator=13701087609, updateTime=1778233940379, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1259567696174301345, tenantId=1146029695717560320, journalId=1259198908832956435, issueId=1259565961842123095, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1259567696174301346, tenantId=1146029695717560320, journalId=1259198908832956435, issueId=1259565961842123095, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=143, endPage=152, ext={EN=ArticleExt(id=1259565965960950528, articleId=1259565965453439741, tenantId=1146029695717560320, journalId=1259198908832956435, language=EN, title=Analysis and prediction of trends in the incidence and mortality of infectious diarrhea in China from 1990 to 2021, columnId=1259565965784789759, journalTitle=Chinese Journal of Disease Control and Prevention, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the trends in the incidence and mortality of infectious diarrhea in China from 1990 to 2021 and predict the incidence and mortality rates for 2022 to 2026, providing evidence for surveillance and prevention strategies.

Methods

Data on the incidence and mortality of infectious diarrhea in China from 1990 to 2021 was collected from the 2021 Global Burden of Disease (GBD 2021) database. The Joinpoint regression model was used to analyze temporal trends in incidence and mortality. The age-period-cohort model was applied to explore the age, period, and cohort effects on the risk of incidence and mortality. An autoregressive integrated moving average (ARIMA) model was used to predict the incidence and mortality rates of infectious diarrhea in China from 2022 to 2026.

Results

Joinpoint regression analysis revealed that from 1990 to 2021, the total, male, and female incidence rates of infectious diarrhea in China showed a declining trend (all P < 0.05), with a slower decrease before 2000 and a more rapid decline thereafter. Total, male, and female mortality rates also declined (all P < 0.05), with a faster decrease prior to 2014 and a slower decline after 2014. Age-period-cohort model analysis revealed that the age effects on incidence and mortality risks for the total, male, and female first decreased and then increased. The RRs of incidence decreased from high values of 2.432, 3.364, and 2.002 in the 0- < 5 age group to the lowest values of 0.478, 0.535, and 0.451 in the 25- < 30 age group. After that, it rose to peak values of 3.204, 2.523, and 3.774 in the ≥85 age group, with all P < 0.001. The RRs of mortality decreased from high values of 3.403, 3.084, and 4.312 in the 0- < 5 age group to the lowest values of 0.061, 0.063, and 0.071 in the 15- < 20 age group, and subsequently increased to peak values of 131.617, 134.317, and 133.610 in the ≥85 age group, with all P < 0.001. The period effects showed a decline trend, with both incidence and mortality RRs reaching their lowest values in 2017-2021, at 0.521, 0.582, 0.498 and 0.273, 0.283, 0.265, respectively, with all P < 0.001. The cohort effects initially increased and then decreased. The RRs of incidence rose from the lowest values of 0.254, 0.312, and 0.214 in 1907-1911 (all P < 0.001) to peak values of 1.868, 1.493, and 2.142 in 1997-2001 (P < 0.001 for the total population and females, P=0.009 for males), and then decreased to low values of 1.212, 0.873, and 1.352 in 2017-2021 (all P>0.05). The RRs of mortality increased from low values of 0.144, 0.165, and 0.143 in 1907-1911 (all P < 0.001) to peak values of 3.613, 3.265, and 3.584 in 2002-2006 (all P < 0.001), and then decreased to low values of 2.315, 2.054, and 2.313 in 2017-2021 (P=0.011 for the total population, P=0.027 for males, P=0.016 for females). Predictions from the ARIMA model suggested that from 2022 to 2026, the incidence of infectious diarrhea in China is projected to show an upward trend, while mortality is expected to continue declining.

Conclusions

The incidence and mortality of infectious diarrhea in China are influenced by age, period, and cohort effects. While the incidence shows an upward trend, mortality continues to decline. Children and the elderly remain high-risk populations for both onset and death. Targeted prevention strategies should be implemented to reduce the disease burden of infectious diarrhea.

, correspAuthors=Dongming ZHOU, Qiong CHEN, authorNote=null, correspAuthorsNote=
ZHOU Dongming, E-mail:
CHEN Qiong, E-mail:
, copyrightStatement=Copyright © 2026 Chinese Journal of Disease Control & Prevention. 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, authorCompany=null, fund=null, authors=null, authorsList=Yuhao WANG, Ting YANG, Zhou XU, Hui LI, You HAN, Dongming ZHOU, Qiong CHEN), CN=ArticleExt(id=1259565970138477328, articleId=1259565965453439741, tenantId=1146029695717560320, journalId=1259198908832956435, language=CN, title=1990—2021年中国感染性腹泻发病与死亡变化趋势分析及预测研究, columnId=1259565966174860033, journalTitle=中华疾病控制杂志, columnName=论著, runingTitle=null, highlight=null, articleAbstract=
目的

分析1990―2021年中国感染性腹泻的发病与死亡变化趋势,并预测2022―2026年的发病率和死亡率,为感染性腹泻的监测和防控提供参考依据。

方法

基于2021年全球疾病负担(Global Burden of Disease, GBD)数据库获得1990―2021年中国感染性腹泻的发病和死亡数据,采用Joinpoint回归模型分析发病和死亡的时间变化趋势; 采用年龄-时期-队列模型探究感染性腹泻发病和死亡风险的年龄、时期、队列效应; 通过自回归移动平均(autoregressive integrated moving average, ARIMA)模型预测2022―2026年中国感染性腹泻的发病率和死亡率。

结果

Joinpoint回归模型结果显示,1990―2021年中国感染性腹泻的总人群、男性及女性发病率均呈下降趋势(均P<0.05),2000年前发病率下降较慢,2000年后发病率下降加快; 总人群、男性、女性死亡率呈下降趋势(均P<0.05),2014年前下降较快,2014年后下降减慢; 年龄-时期-队列模型结果显示,总人群、男性、女性的发病和死亡风险年龄效应呈现先下降后上升的趋势,发病率RR从0~<5岁组的高值(2.432、3.364、2.002)下降至25~<30岁组的最低值(0.478、0.535、0.451),而后上升至≥85岁组的峰值(3.204、2.523、3.774),均P < 0.001。死亡率RR从0~<5岁组的高值(3.403、3.084、4.312)下降至15~<20岁组的最低值(0.061、0.063、0.071),而后上升至≥85岁组的峰值(131.617、134.317、133.610),均P < 0.001。时期效应呈下降趋势,发病率和死亡率RR均降至2017―2021年的最低值,分别为0.521、0.582、0.498和0.273、0.283、0.265,均P < 0.001。队列效应呈现先升高后下降趋势,发病率RR从1907―1911年的最低值[0.254、0.312、0.214(均P < 0.001)]升高至1997―2001年的峰值[1.868、1.493、2.142(总人群、女性P < 0.001,男性P=0.009)],而后下降至2017―2021年的低值[1.212、0.873、1.352(均P>0.05)]。死亡率RR从1907—1911年的低值[0.144、0.165、0.143(均P < 0.001)]升高至2002―2006年的峰值[3.613、3.265、3.584(均P < 0.001)],而后下降至2017―2021年的低值[2.315、2.054、2.313(总人群P=0.011,男性P=0.027,女性P=0.016)]。ARIMA模型预测结果显示,2022―2026年中国感染性腹泻发病率呈上升趋势,死亡率呈下降趋势。

结论

中国感染性腹泻发病和死亡受年龄-时期-队列等因素影响,发病率有上升趋势,死亡率持续下降,儿童和老年人是发病和死亡风险较高的人群,应采取精准防控措施降低感染性腹泻的疾病负担。

, correspAuthors=周东明, 陈琼, authorNote=null, correspAuthorsNote=
周东明,E-mail:
陈琼,E-mail:
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A:发病率变化趋势;B:死亡率变化趋势。

, figureFileSmall=sT4Sj8CQWR9Bq1B3H9Li/w==, figureFileBig=cKzE7OY5QYkoXzrgf+WwEQ==, tableContent=null), ArticleFig(id=1259565990279525289, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=EN, label=Figure 2, caption=RR analysis of infectious diarrhea incidence in China from 1990 to 2021, figureFileSmall=mwNOQquLdYBCdX8ghcid1g==, figureFileBig=Xx0GwUSfNWMtEgKtMI4Pnw==, tableContent=null), ArticleFig(id=1259565990933836717, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=CN, label=图2, caption=1990―2021年中国感染性腹泻发病率RR分析

A:年龄;B:时期;C:队列。

, figureFileSmall=mwNOQquLdYBCdX8ghcid1g==, figureFileBig=Xx0GwUSfNWMtEgKtMI4Pnw==, tableContent=null), ArticleFig(id=1259565991403598769, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=EN, label=Figure 3, caption=RR analysis of infectious diarrhea mortality in China from 1990 to 2021, figureFileSmall=ICDa2wc2InICFvtg06YMTw==, figureFileBig=4eSvjtXdNLNPCUrwY2/fEw==, tableContent=null), ArticleFig(id=1259565991772697524, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=CN, label=图3, caption=1990―2021年中国感染性腹泻死亡率RR分析

A:年龄;B:时期;C:队列。

, figureFileSmall=ICDa2wc2InICFvtg06YMTw==, figureFileBig=4eSvjtXdNLNPCUrwY2/fEw==, tableContent=null), ArticleFig(id=1259565991944663991, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=EN, label=Table 1, caption=

Age-period-cohort model analysis of infectious diarrhea incidence in China from 1990 to 2021

, figureFileSmall=null, figureFileBig=null, tableContent=
变量
Variable
总人群Total population男性Male女性Female
RR值value
(95% CI)
P
value
RR值value
(95% CI)
P
value
RR值value
(95% CI)
P
value
年龄效应/岁Age effect/years
  0~<52.432(1.762~3.364)< 0.0013.364(2.415~4.696)< 0.0012.002(1.432~2.794)< 0.001
  5~<101.503(1.123~2.014)0.0062.056(1.525~2.774)< 0.0011.213(0.904~1.646)0.209
  10~<150.924(0.717~1.198)0.5341.217(0.938~1.571)0.1550.764(0.595~0.996)0.044
  15~<200.613(0.494~0.765)< 0.0010.752(0.604~0.943)< 0.0010.547(0.437~0.674)0.011
  20~<250.497(0.415~0.584)< 0.0010.563(0.471~0.672)< 0.0010.459(0.373~0.541)< 0.001
  25~<300.478(0.416~0.543)< 0.0010.535(0.463~0.618)< 0.0010.451(0.394~0.513)< 0.001
  30~<350.512(0.467~0.579)< 0.0010.567(0.502~0.624)< 0.0010.493(0.442~0.545)< 0.001
  35~<400.573(0.536~0.617)< 0.0010.608(0.565~0.649)< 0.0010.556(0.527~0.598)< 0.001
  40~<450.639(0.617~0.659)< 0.0010.632(0.616~0.658)< 0.0010.631(0.604~0.657)< 0.001
  45~<500.694(0.677~0.725)< 0.0010.673(0.644~0.698)< 0.0010.713(0.685~0.746)< 0.001
  50~<550.776(0.728~0.823)< 0.0010.711(0.672~0.763)< 0.0010.812(0.753~0.865)< 0.001
  55~<600.875(0.792~0.961)0.0070.777(0.702~0.863)< 0.0010.943(0.854~1.047)0.238
  60~<651.023(0.897~1.172)0.7790.874(0.766~1.005)0.0561.136(0.987~1.308)0.092
  65~<701.231(1.033~1.462)0.0231.016(0.854~1.228)0.8791.383(1.155~1.664)< 0.001
  70~<751.484(1.195~1.836)< 0.0011.195(0.952~1.494)0.1231.682(1.344~2.105)< 0.001
  75~<801.802(1.405~2.337)< 0.0011.434(1.102~1.867)0.0082.077(1.593~2.698)< 0.001
  80~<852.337(1.747~3.128)< 0.0011.844(1.363~2.487)< 0.0012.715(2.016~3.661)< 0.001
  ≥853.204(2.316~4.427)< 0.0012.523(1.812~3.528)< 0.0013.774(2.705~5.262)< 0.001
时期效应/年份Period effect/year
  1992―19962.172(1.945~2.442)< 0.0011.924(1.703~2.165)< 0.0012.372(2.114~2.676)< 0.001
  1997―20011.658(1.545~1.771)< 0.0011.513(1.407~1.628)< 0.0011.774(1.655~1.907)< 0.001
  2002―20061.358(1.305~1.407)< 0.0011.402(1.353~1.467)< 0.0011.282(1.237~1.338)< 0.001
  2007―20110.913(0.896~0.947)< 0.0010.944(0.912~0.968)< 0.0010.893(0.872~0.924)< 0.001
  2012―20160.625(0.586~0.657)< 0.0010.673(0.635~0.718)< 0.0010.583(0.552~0.615)< 0.001
  2017―20210.521(0.484~0.573)< 0.0010.582(0.533~0.647)< 0.0010.498(0.442~0.533)< 0.001
出生队列效应/年份Birth cohort effect/year
  1907―19110.254(0.176~0.369)< 0.0010.312(0.214~0.465)< 0.0010.214(0.141~0.315)< 0.001
  1912―19160.293(0.205~0.433)< 0.0010.386(0.266~0.563)< 0.0010.257(0.176~0.373)< 0.001
  1917―19210.353(0.245~0.504)< 0.0010.461(0.324~0.668)< 0.0010.305(0.217~0.434)< 0.001
  1922―19260.416(0.303~0.572)< 0.0010.542(0.393~0.765)< 0.0010.358(0.264~0.492)< 0.001
  1927―19310.484(0.374~0.642)< 0.0010.633(0.482~0.847)< 0.0010.426(0.312~0.554)0.001
  1932―19360.552(0.442~0.695)< 0.0010.716(0.566~0.894)< 0.0010.475(0.373~0.607)< 0.001
  1937―19410.612(0.513~0.743)< 0.0010.762(0.623~0.933)0.0080.533(0.442~0.657)< 0.001
  1942―19460.684(0.584~0.803)< 0.0010.827(0.694~0.967)< 0.0010.613(0.542~0.726)0.015
  1947―19510.776(0.686~0.874)< 0.0010.882(0.783~1.004)0.0460.714(0.625~0.802)< 0.001
  1952―19560.882(0.813~0.967)0.0020.963(0.885~1.056)0.3560.846(0.778~0.912)< 0.001
  1957―19611.011(0.973~1.062)0.6141.052(1.005~1.104)0.0401.002(0.951~1.056)0.960
  1962―19661.152(1.113~1.184)< 0.0011.141(1.102~1.176)< 0.0011.172(1.134~1.203)< 0.001
  1967―19711.284(1.224~1.345)< 0.0011.217(1.167~1.274)< 0.0011.342(1.283~1.406)< 0.001
  1972―19761.423(1.314~1.533)< 0.0011.296(1.193~1.407)< 0.0011.527(1.403~1.657)< 0.001
  1977―19811.564(1.388~1.769)< 0.0011.362(1.201~1.548)< 0.0011.724(1.511~1.945)< 0.001
  1982―19861.698(1.445~1.982)< 0.0011.434(1.215~1.686)< 0.0011.903(1.614~2.248)< 0.001
  1987―19911.795(1.486~2.188)< 0.0011.478(1.213~1.807)< 0.0012.056(1.683~2.501)< 0.001
  1992―19961.862(1.487~2.332)< 0.0011.482(1.173~1.889)0.0012.137(1.684~2.709)< 0.001
  1997―20011.868(1.424~2.449)< 0.0011.493(1.102~1.928)0.0092.142(1.606~2.818)< 0.001
  2002―20061.787(1.302~2.454)< 0.0011.374(0.993~1.907)0.0612.033(1.462~2.815)< 0.001
  2007―20111.648(1.155~2.342)0.0071.237(0.854~1.776)0.2701.844(1.287~2.669)0.001
  2012―20161.423(0.975~2.063)0.0711.048(0.705~1.537)0.8521.591(1.077~2.343)0.021
  2017―20211.212(0.824~1.786)0.3330.873(0.584~1.296)0.4771.352(0.914~2.018)0.139
), ArticleFig(id=1259565992301179833, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=CN, label=表1, caption=

1990―2021年中国感染性腹泻发病率年龄-时期-队列模型分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量
Variable
总人群Total population男性Male女性Female
RR值value
(95% CI)
P
value
RR值value
(95% CI)
P
value
RR值value
(95% CI)
P
value
年龄效应/岁Age effect/years
  0~<52.432(1.762~3.364)< 0.0013.364(2.415~4.696)< 0.0012.002(1.432~2.794)< 0.001
  5~<101.503(1.123~2.014)0.0062.056(1.525~2.774)< 0.0011.213(0.904~1.646)0.209
  10~<150.924(0.717~1.198)0.5341.217(0.938~1.571)0.1550.764(0.595~0.996)0.044
  15~<200.613(0.494~0.765)< 0.0010.752(0.604~0.943)< 0.0010.547(0.437~0.674)0.011
  20~<250.497(0.415~0.584)< 0.0010.563(0.471~0.672)< 0.0010.459(0.373~0.541)< 0.001
  25~<300.478(0.416~0.543)< 0.0010.535(0.463~0.618)< 0.0010.451(0.394~0.513)< 0.001
  30~<350.512(0.467~0.579)< 0.0010.567(0.502~0.624)< 0.0010.493(0.442~0.545)< 0.001
  35~<400.573(0.536~0.617)< 0.0010.608(0.565~0.649)< 0.0010.556(0.527~0.598)< 0.001
  40~<450.639(0.617~0.659)< 0.0010.632(0.616~0.658)< 0.0010.631(0.604~0.657)< 0.001
  45~<500.694(0.677~0.725)< 0.0010.673(0.644~0.698)< 0.0010.713(0.685~0.746)< 0.001
  50~<550.776(0.728~0.823)< 0.0010.711(0.672~0.763)< 0.0010.812(0.753~0.865)< 0.001
  55~<600.875(0.792~0.961)0.0070.777(0.702~0.863)< 0.0010.943(0.854~1.047)0.238
  60~<651.023(0.897~1.172)0.7790.874(0.766~1.005)0.0561.136(0.987~1.308)0.092
  65~<701.231(1.033~1.462)0.0231.016(0.854~1.228)0.8791.383(1.155~1.664)< 0.001
  70~<751.484(1.195~1.836)< 0.0011.195(0.952~1.494)0.1231.682(1.344~2.105)< 0.001
  75~<801.802(1.405~2.337)< 0.0011.434(1.102~1.867)0.0082.077(1.593~2.698)< 0.001
  80~<852.337(1.747~3.128)< 0.0011.844(1.363~2.487)< 0.0012.715(2.016~3.661)< 0.001
  ≥853.204(2.316~4.427)< 0.0012.523(1.812~3.528)< 0.0013.774(2.705~5.262)< 0.001
时期效应/年份Period effect/year
  1992―19962.172(1.945~2.442)< 0.0011.924(1.703~2.165)< 0.0012.372(2.114~2.676)< 0.001
  1997―20011.658(1.545~1.771)< 0.0011.513(1.407~1.628)< 0.0011.774(1.655~1.907)< 0.001
  2002―20061.358(1.305~1.407)< 0.0011.402(1.353~1.467)< 0.0011.282(1.237~1.338)< 0.001
  2007―20110.913(0.896~0.947)< 0.0010.944(0.912~0.968)< 0.0010.893(0.872~0.924)< 0.001
  2012―20160.625(0.586~0.657)< 0.0010.673(0.635~0.718)< 0.0010.583(0.552~0.615)< 0.001
  2017―20210.521(0.484~0.573)< 0.0010.582(0.533~0.647)< 0.0010.498(0.442~0.533)< 0.001
出生队列效应/年份Birth cohort effect/year
  1907―19110.254(0.176~0.369)< 0.0010.312(0.214~0.465)< 0.0010.214(0.141~0.315)< 0.001
  1912―19160.293(0.205~0.433)< 0.0010.386(0.266~0.563)< 0.0010.257(0.176~0.373)< 0.001
  1917―19210.353(0.245~0.504)< 0.0010.461(0.324~0.668)< 0.0010.305(0.217~0.434)< 0.001
  1922―19260.416(0.303~0.572)< 0.0010.542(0.393~0.765)< 0.0010.358(0.264~0.492)< 0.001
  1927―19310.484(0.374~0.642)< 0.0010.633(0.482~0.847)< 0.0010.426(0.312~0.554)0.001
  1932―19360.552(0.442~0.695)< 0.0010.716(0.566~0.894)< 0.0010.475(0.373~0.607)< 0.001
  1937―19410.612(0.513~0.743)< 0.0010.762(0.623~0.933)0.0080.533(0.442~0.657)< 0.001
  1942―19460.684(0.584~0.803)< 0.0010.827(0.694~0.967)< 0.0010.613(0.542~0.726)0.015
  1947―19510.776(0.686~0.874)< 0.0010.882(0.783~1.004)0.0460.714(0.625~0.802)< 0.001
  1952―19560.882(0.813~0.967)0.0020.963(0.885~1.056)0.3560.846(0.778~0.912)< 0.001
  1957―19611.011(0.973~1.062)0.6141.052(1.005~1.104)0.0401.002(0.951~1.056)0.960
  1962―19661.152(1.113~1.184)< 0.0011.141(1.102~1.176)< 0.0011.172(1.134~1.203)< 0.001
  1967―19711.284(1.224~1.345)< 0.0011.217(1.167~1.274)< 0.0011.342(1.283~1.406)< 0.001
  1972―19761.423(1.314~1.533)< 0.0011.296(1.193~1.407)< 0.0011.527(1.403~1.657)< 0.001
  1977―19811.564(1.388~1.769)< 0.0011.362(1.201~1.548)< 0.0011.724(1.511~1.945)< 0.001
  1982―19861.698(1.445~1.982)< 0.0011.434(1.215~1.686)< 0.0011.903(1.614~2.248)< 0.001
  1987―19911.795(1.486~2.188)< 0.0011.478(1.213~1.807)< 0.0012.056(1.683~2.501)< 0.001
  1992―19961.862(1.487~2.332)< 0.0011.482(1.173~1.889)0.0012.137(1.684~2.709)< 0.001
  1997―20011.868(1.424~2.449)< 0.0011.493(1.102~1.928)0.0092.142(1.606~2.818)< 0.001
  2002―20061.787(1.302~2.454)< 0.0011.374(0.993~1.907)0.0612.033(1.462~2.815)< 0.001
  2007―20111.648(1.155~2.342)0.0071.237(0.854~1.776)0.2701.844(1.287~2.669)0.001
  2012―20161.423(0.975~2.063)0.0711.048(0.705~1.537)0.8521.591(1.077~2.343)0.021
  2017―20211.212(0.824~1.786)0.3330.873(0.584~1.296)0.4771.352(0.914~2.018)0.139
), ArticleFig(id=1259565992687055805, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=EN, label=Table 2, caption=

Age-period-cohort model analysis of infectious diarrhea mortality in China from 1990 to 2021

, figureFileSmall=null, figureFileBig=null, tableContent=
变量
Variable
总人群Total population男性Male女性Female
RR值value
(95% CI)
P
value
RR值value
(95% CI)
P
value
RR值value
(95% CI)
P
value
年龄效应/岁Age effect/years
  0~<53.403(1.974~5.876)< 0.0013.084(1.815~5.247)< 0.0014.312(2.433~7.654)< 0.001
  5~<100.262(0.164~0.437)< 0.0010.263(0.164~0.426)< 0.0010.292(0.176~0.498)< 0.001
  10~<150.073(0.048~0.116)< 0.0010.075(0.056~0.118)< 0.0010.078(0.054~0.123)< 0.001
  15~<200.061(0.052~0.098)< 0.0010.063(0.045~0.097)< 0.0010.071(0.057~0.110)< 0.001
  20~<250.095(0.073~0.126)< 0.0010.094(0.076~0.123)< 0.0010.095(0.076~0.132)< 0.001
  25~<300.104(0.082~0.125)< 0.0010.107(0.083~0.138)< 0.0010.098(0.076~0.122)< 0.001
  30~<350.123(0.104~0.146)< 0.0010.134(0.116~0.163)< 0.0010.118(0.098~0.132)< 0.001
  35~<400.207(0.188~0.225)< 0.0010.215(0.192~0.248)< 0.0010.176(0.164~0.208)< 0.001
  40~<450.334(0.312~0.353)< 0.0010.364(0.346~0.385)< 0.0010.293(0.287~0.317)< 0.001
  45~<500.476(0.445~0.507)< 0.0010.514(0.485~0.548)< 0.0010.412(0.387~0.443)< 0.001
  50~<550.682(0.607~0.758)< 0.0010.713(0.644~0.796)< 0.0010.603(0.532~0.676)< 0.001
  55~<601.203(1.015~1.426)0.0371.215(1.036~1.437)0.0221.108(0.921~1.322)0.277
  60~<652.296(1.822~2.895)< 0.0012.266(1.813~2.847)< 0.0012.187(1.710~2.787)< 0.001
  65~<704.113(3.065~5.538)< 0.0014.005(3.007~5.345)< 0.0013.987(2.912~5.443)< 0.001
  70~<757.993(5.564~11.497)< 0.0017.386(5.186~10.520)< 0.0018.143(5.554~11.943)< 0.001
  75~<8019.225(12.516~29.535)< 0.00116.724(11.006~25.427)0.00821.054(13.398~33.107)< 0.001
  80~<8551.164(31.365~83.466)< 0.00145.745(28.384~73.706)< 0.00156.396(33.687~94.416)< 0.001
  ≥85131.617(76.348~226.913)< 0.001134.317(78.983~228.406)< 0.001133.610(75.304~237.087)< 0.001
时期效应/年份Period effect/year
  1992―19963.485(3.073~3.955)< 0.0013.344(2.955~3.786)< 0.0013.576(3.132~4.087)< 0.001
  1997―20013.043(2.714~3.418)< 0.0012.922(2.612~3.276)< 0.0013.121(2.765~3.523)< 0.001
  2002―20061.113(1.075~1.518)< 0.0011.104(1.065~1.143)< 0.0011.124(1.087~1.176)< 0.001
  2007―20110.542(0.513~0.576)< 0.0010.554(0.521~0.587)< 0.0010.543(0.519~0.576)< 0.001
  2012―20160.394(0.366~0.439)< 0.0010.410(0.376~0.454)< 0.0010.387(0.354~0.424)< 0.001
  2017―20210.273(0.235~0.317)< 0.0010.283(0.243~0.332)< 0.0010.265(0.221~0.305)< 0.001
出生队列效应/年份Birth cohort effect/year
  1907―19110.144(0.083~0.276)< 0.0010.165(0.098~0.310)< 0.0010.143(0.076~0.287)< 0.001
  1912―19160.186(0.103~0.348)< 0.0010.212(0.119~0.387)< 0.0010.187(0.095~0.354)< 0.001
  1917―19210.225(0.122~0.407)< 0.0010.254(0.145~0.456)< 0.0010.222(0.121~0.413)< 0.001
  1922―19260.277(0.162~0.454)< 0.0010.303(0.187~0.504)< 0.0010.265(0.154~0.465)< 0.001
  1927―19310.311(0.203~0.508)< 0.0010.343(0.223~0.543)< 0.0010.316(0.198~0.504)< 0.001
  1932―19360.373(0.254~0.557)< 0.0010.406(0.276~0.587)< 0.0010.376(0.254~0.563)< 0.001
  1937―19410.444(0.322~0.627)< 0.0010.465(0.343~0.644)< 0.0010.454(0.321~0.643)< 0.001
  1942―19460.533(0.403~0.696)< 0.0010.554(0.421~0.712)< 0.0010.547(0.418~0.722)< 0.001
  1947―19510.622(0.513~0.765)< 0.0010.643(0.523~0.784)< 0.0010.643(0.514~0.798)< 0.001
  1952―19560.731(0.633~0.836)< 0.0010.745(0.654~0.843)< 0.0010.743(0.643~0.865)< 0.001
  1957―19610.856(0.793~0.925)< 0.0010.866(0.802~0.929)< 0.0010.876(0.802~0.943)< 0.001
  1962―19661.026(0.974~1.078)0.3941.021(0.976~1.065)0.4771.032(0.983~1.097)0.209
  1967―19711.235(1.144~1.337)< 0.0011.221(1.132~1.310)< 0.0011.232(1.142~1.345)< 0.001
  1972―19761.485(1.297~1.698)< 0.0011.465(1.287~1.676)< 0.0011.463(1.265~1.687)< 0.001
  1977―19811.767(1.434~2.158)< 0.0011.721(1.410~2.106)< 0.0011.721(1.394~2.132)< 0.001
  1982―19862.075(1.583~2.717)< 0.0012.003(1.543~2.602)< 0.0012.034(1.532~2.705)< 0.001
  1987―19912.464(1.785~3.416)< 0.0012.332(1.703~3.201)< 0.0012.443(1.732~3.443)< 0.001
  1992―19962.932(1.997~4.314)< 0.0012.723(1.874~3.955)< 0.0012.934(1.956~4.398)< 0.001
  1997―20013.384(2.143~5.346)< 0.0013.098(1.987~4.821)< 0.0013.383(2.096~5.476)< 0.001
  2002―20063.613(2.114~6.167)< 0.0013.265(1.943~5.504)< 0.0013.584(2.043~6.302)< 0.001
  2007―20113.444(1.893~6.277)< 0.0013.106(1.732~5.567)< 0.0013.404(1.815~6.398)< 0.001
  2012―20162.888(1.535~5.457)0.0712.584(1.395~4.807)0.0032.866(1.467~5.593)0.002
  2017―20212.315(1.212~4.428)0.0112.054(1.092~3.856)0.0272.313(1.174~4.587)0.016
), ArticleFig(id=1259565993098097601, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=CN, label=表2, caption=

1990―2021年中国感染性腹泻死亡率年龄-时期-队列模型分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量
Variable
总人群Total population男性Male女性Female
RR值value
(95% CI)
P
value
RR值value
(95% CI)
P
value
RR值value
(95% CI)
P
value
年龄效应/岁Age effect/years
  0~<53.403(1.974~5.876)< 0.0013.084(1.815~5.247)< 0.0014.312(2.433~7.654)< 0.001
  5~<100.262(0.164~0.437)< 0.0010.263(0.164~0.426)< 0.0010.292(0.176~0.498)< 0.001
  10~<150.073(0.048~0.116)< 0.0010.075(0.056~0.118)< 0.0010.078(0.054~0.123)< 0.001
  15~<200.061(0.052~0.098)< 0.0010.063(0.045~0.097)< 0.0010.071(0.057~0.110)< 0.001
  20~<250.095(0.073~0.126)< 0.0010.094(0.076~0.123)< 0.0010.095(0.076~0.132)< 0.001
  25~<300.104(0.082~0.125)< 0.0010.107(0.083~0.138)< 0.0010.098(0.076~0.122)< 0.001
  30~<350.123(0.104~0.146)< 0.0010.134(0.116~0.163)< 0.0010.118(0.098~0.132)< 0.001
  35~<400.207(0.188~0.225)< 0.0010.215(0.192~0.248)< 0.0010.176(0.164~0.208)< 0.001
  40~<450.334(0.312~0.353)< 0.0010.364(0.346~0.385)< 0.0010.293(0.287~0.317)< 0.001
  45~<500.476(0.445~0.507)< 0.0010.514(0.485~0.548)< 0.0010.412(0.387~0.443)< 0.001
  50~<550.682(0.607~0.758)< 0.0010.713(0.644~0.796)< 0.0010.603(0.532~0.676)< 0.001
  55~<601.203(1.015~1.426)0.0371.215(1.036~1.437)0.0221.108(0.921~1.322)0.277
  60~<652.296(1.822~2.895)< 0.0012.266(1.813~2.847)< 0.0012.187(1.710~2.787)< 0.001
  65~<704.113(3.065~5.538)< 0.0014.005(3.007~5.345)< 0.0013.987(2.912~5.443)< 0.001
  70~<757.993(5.564~11.497)< 0.0017.386(5.186~10.520)< 0.0018.143(5.554~11.943)< 0.001
  75~<8019.225(12.516~29.535)< 0.00116.724(11.006~25.427)0.00821.054(13.398~33.107)< 0.001
  80~<8551.164(31.365~83.466)< 0.00145.745(28.384~73.706)< 0.00156.396(33.687~94.416)< 0.001
  ≥85131.617(76.348~226.913)< 0.001134.317(78.983~228.406)< 0.001133.610(75.304~237.087)< 0.001
时期效应/年份Period effect/year
  1992―19963.485(3.073~3.955)< 0.0013.344(2.955~3.786)< 0.0013.576(3.132~4.087)< 0.001
  1997―20013.043(2.714~3.418)< 0.0012.922(2.612~3.276)< 0.0013.121(2.765~3.523)< 0.001
  2002―20061.113(1.075~1.518)< 0.0011.104(1.065~1.143)< 0.0011.124(1.087~1.176)< 0.001
  2007―20110.542(0.513~0.576)< 0.0010.554(0.521~0.587)< 0.0010.543(0.519~0.576)< 0.001
  2012―20160.394(0.366~0.439)< 0.0010.410(0.376~0.454)< 0.0010.387(0.354~0.424)< 0.001
  2017―20210.273(0.235~0.317)< 0.0010.283(0.243~0.332)< 0.0010.265(0.221~0.305)< 0.001
出生队列效应/年份Birth cohort effect/year
  1907―19110.144(0.083~0.276)< 0.0010.165(0.098~0.310)< 0.0010.143(0.076~0.287)< 0.001
  1912―19160.186(0.103~0.348)< 0.0010.212(0.119~0.387)< 0.0010.187(0.095~0.354)< 0.001
  1917―19210.225(0.122~0.407)< 0.0010.254(0.145~0.456)< 0.0010.222(0.121~0.413)< 0.001
  1922―19260.277(0.162~0.454)< 0.0010.303(0.187~0.504)< 0.0010.265(0.154~0.465)< 0.001
  1927―19310.311(0.203~0.508)< 0.0010.343(0.223~0.543)< 0.0010.316(0.198~0.504)< 0.001
  1932―19360.373(0.254~0.557)< 0.0010.406(0.276~0.587)< 0.0010.376(0.254~0.563)< 0.001
  1937―19410.444(0.322~0.627)< 0.0010.465(0.343~0.644)< 0.0010.454(0.321~0.643)< 0.001
  1942―19460.533(0.403~0.696)< 0.0010.554(0.421~0.712)< 0.0010.547(0.418~0.722)< 0.001
  1947―19510.622(0.513~0.765)< 0.0010.643(0.523~0.784)< 0.0010.643(0.514~0.798)< 0.001
  1952―19560.731(0.633~0.836)< 0.0010.745(0.654~0.843)< 0.0010.743(0.643~0.865)< 0.001
  1957―19610.856(0.793~0.925)< 0.0010.866(0.802~0.929)< 0.0010.876(0.802~0.943)< 0.001
  1962―19661.026(0.974~1.078)0.3941.021(0.976~1.065)0.4771.032(0.983~1.097)0.209
  1967―19711.235(1.144~1.337)< 0.0011.221(1.132~1.310)< 0.0011.232(1.142~1.345)< 0.001
  1972―19761.485(1.297~1.698)< 0.0011.465(1.287~1.676)< 0.0011.463(1.265~1.687)< 0.001
  1977―19811.767(1.434~2.158)< 0.0011.721(1.410~2.106)< 0.0011.721(1.394~2.132)< 0.001
  1982―19862.075(1.583~2.717)< 0.0012.003(1.543~2.602)< 0.0012.034(1.532~2.705)< 0.001
  1987―19912.464(1.785~3.416)< 0.0012.332(1.703~3.201)< 0.0012.443(1.732~3.443)< 0.001
  1992―19962.932(1.997~4.314)< 0.0012.723(1.874~3.955)< 0.0012.934(1.956~4.398)< 0.001
  1997―20013.384(2.143~5.346)< 0.0013.098(1.987~4.821)< 0.0013.383(2.096~5.476)< 0.001
  2002―20063.613(2.114~6.167)< 0.0013.265(1.943~5.504)< 0.0013.584(2.043~6.302)< 0.001
  2007―20113.444(1.893~6.277)< 0.0013.106(1.732~5.567)< 0.0013.404(1.815~6.398)< 0.001
  2012―20162.888(1.535~5.457)0.0712.584(1.395~4.807)0.0032.866(1.467~5.593)0.002
  2017―20212.315(1.212~4.428)0.0112.054(1.092~3.856)0.0272.313(1.174~4.587)0.016
), ArticleFig(id=1259565993504945092, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=EN, label=Table 3, caption=

Predicted incidence and mortality rates of infectious diarrhea in China from 2022 to 2026

, figureFileSmall=null, figureFileBig=null, tableContent=
年份
Year
发病率Incidence rate/100 000-1 (95% CI)死亡率Mortality rate/100 000-1(95% CI)
总人群Total population男性Male女性Female总人群Total population男性Male女性Female
20224 922(3 300~7 343)5 113(3 522~7 424)4 759(3 375~6 810)8.290(8.070~8.520)9.680(9.460~9.890)7.460(7.230~7.700)
20235 041(2 870~8 854)5 218(3 084~8 830)4 903(3 060~8 075)2.780(2.560 ~3.010)3.030(2.810~3.250)2.600(2.370~2.840)
20245 168(2 602~10 264)5 363(2 560~8 166)5 035(2 904~9 066)1.190(0.967~1.420)1.280(1.060~1.500)1.110(0.881~ 1.350)
20255 300(2 416~11 626)5 499(2 696~8 302)5 157(2 818~9 881)0.538(0.312~0.764)0.585(0.366~0.804)0.488(0.255~0.721)
20265 421(2 297~12 787)5 623(2 819~8 426)5 268(2 768~10 561)0.225(0~0.450)0.257(0.038~0.476)0.185(0~0.418)
), ArticleFig(id=1259565993869849546, tenantId=1146029695717560320, journalId=1259198908832956435, articleId=1259565965453439741, language=CN, label=表3, caption=

2022―2026年中国感染性腹泻发病率和死亡率预测情况

, figureFileSmall=null, figureFileBig=null, tableContent=
年份
Year
发病率Incidence rate/100 000-1 (95% CI)死亡率Mortality rate/100 000-1(95% CI)
总人群Total population男性Male女性Female总人群Total population男性Male女性Female
20224 922(3 300~7 343)5 113(3 522~7 424)4 759(3 375~6 810)8.290(8.070~8.520)9.680(9.460~9.890)7.460(7.230~7.700)
20235 041(2 870~8 854)5 218(3 084~8 830)4 903(3 060~8 075)2.780(2.560 ~3.010)3.030(2.810~3.250)2.600(2.370~2.840)
20245 168(2 602~10 264)5 363(2 560~8 166)5 035(2 904~9 066)1.190(0.967~1.420)1.280(1.060~1.500)1.110(0.881~ 1.350)
20255 300(2 416~11 626)5 499(2 696~8 302)5 157(2 818~9 881)0.538(0.312~0.764)0.585(0.366~0.804)0.488(0.255~0.721)
20265 421(2 297~12 787)5 623(2 819~8 426)5 268(2 768~10 561)0.225(0~0.450)0.257(0.038~0.476)0.185(0~0.418)
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1990—2021年中国感染性腹泻发病与死亡变化趋势分析及预测研究
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王宇皓 , 杨亭 , 徐洲 , 李晖 , 韩有 , 周东明 * , 陈琼 *
中华疾病控制杂志 | 论著 2026,30(2): 143-152
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中华疾病控制杂志 | 论著 2026, 30(2): 143-152
1990—2021年中国感染性腹泻发病与死亡变化趋势分析及预测研究
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王宇皓, 杨亭, 徐洲, 李晖, 韩有, 周东明* , 陈琼*
作者信息
  • 东部战区疾病预防控制中心,南京 210002

通讯作者:

周东明,E-mail:
陈琼,E-mail:
Analysis and prediction of trends in the incidence and mortality of infectious diarrhea in China from 1990 to 2021
Yuhao WANG, Ting YANG, Zhou XU, Hui LI, You HAN, Dongming ZHOU , Qiong CHEN
Affiliations
  • Center for Disease Control and Prevention of Eastern Theater Command, Nanjing 210002, China
出版时间: 2026-02-10 doi: 10.16462/j.cnki.zhjbkz.2026.02.003
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目的

分析1990―2021年中国感染性腹泻的发病与死亡变化趋势,并预测2022―2026年的发病率和死亡率,为感染性腹泻的监测和防控提供参考依据。

方法

基于2021年全球疾病负担(Global Burden of Disease, GBD)数据库获得1990―2021年中国感染性腹泻的发病和死亡数据,采用Joinpoint回归模型分析发病和死亡的时间变化趋势; 采用年龄-时期-队列模型探究感染性腹泻发病和死亡风险的年龄、时期、队列效应; 通过自回归移动平均(autoregressive integrated moving average, ARIMA)模型预测2022―2026年中国感染性腹泻的发病率和死亡率。

结果

Joinpoint回归模型结果显示,1990―2021年中国感染性腹泻的总人群、男性及女性发病率均呈下降趋势(均P<0.05),2000年前发病率下降较慢,2000年后发病率下降加快; 总人群、男性、女性死亡率呈下降趋势(均P<0.05),2014年前下降较快,2014年后下降减慢; 年龄-时期-队列模型结果显示,总人群、男性、女性的发病和死亡风险年龄效应呈现先下降后上升的趋势,发病率RR从0~<5岁组的高值(2.432、3.364、2.002)下降至25~<30岁组的最低值(0.478、0.535、0.451),而后上升至≥85岁组的峰值(3.204、2.523、3.774),均P < 0.001。死亡率RR从0~<5岁组的高值(3.403、3.084、4.312)下降至15~<20岁组的最低值(0.061、0.063、0.071),而后上升至≥85岁组的峰值(131.617、134.317、133.610),均P < 0.001。时期效应呈下降趋势,发病率和死亡率RR均降至2017―2021年的最低值,分别为0.521、0.582、0.498和0.273、0.283、0.265,均P < 0.001。队列效应呈现先升高后下降趋势,发病率RR从1907―1911年的最低值[0.254、0.312、0.214(均P < 0.001)]升高至1997―2001年的峰值[1.868、1.493、2.142(总人群、女性P < 0.001,男性P=0.009)],而后下降至2017―2021年的低值[1.212、0.873、1.352(均P>0.05)]。死亡率RR从1907—1911年的低值[0.144、0.165、0.143(均P < 0.001)]升高至2002―2006年的峰值[3.613、3.265、3.584(均P < 0.001)],而后下降至2017―2021年的低值[2.315、2.054、2.313(总人群P=0.011,男性P=0.027,女性P=0.016)]。ARIMA模型预测结果显示,2022―2026年中国感染性腹泻发病率呈上升趋势,死亡率呈下降趋势。

结论

中国感染性腹泻发病和死亡受年龄-时期-队列等因素影响,发病率有上升趋势,死亡率持续下降,儿童和老年人是发病和死亡风险较高的人群,应采取精准防控措施降低感染性腹泻的疾病负担。

感染性腹泻  /  趋势  /  年龄-时期-队列模型  /  预测
Objective

To analyze the trends in the incidence and mortality of infectious diarrhea in China from 1990 to 2021 and predict the incidence and mortality rates for 2022 to 2026, providing evidence for surveillance and prevention strategies.

Methods

Data on the incidence and mortality of infectious diarrhea in China from 1990 to 2021 was collected from the 2021 Global Burden of Disease (GBD 2021) database. The Joinpoint regression model was used to analyze temporal trends in incidence and mortality. The age-period-cohort model was applied to explore the age, period, and cohort effects on the risk of incidence and mortality. An autoregressive integrated moving average (ARIMA) model was used to predict the incidence and mortality rates of infectious diarrhea in China from 2022 to 2026.

Results

Joinpoint regression analysis revealed that from 1990 to 2021, the total, male, and female incidence rates of infectious diarrhea in China showed a declining trend (all P < 0.05), with a slower decrease before 2000 and a more rapid decline thereafter. Total, male, and female mortality rates also declined (all P < 0.05), with a faster decrease prior to 2014 and a slower decline after 2014. Age-period-cohort model analysis revealed that the age effects on incidence and mortality risks for the total, male, and female first decreased and then increased. The RRs of incidence decreased from high values of 2.432, 3.364, and 2.002 in the 0- < 5 age group to the lowest values of 0.478, 0.535, and 0.451 in the 25- < 30 age group. After that, it rose to peak values of 3.204, 2.523, and 3.774 in the ≥85 age group, with all P < 0.001. The RRs of mortality decreased from high values of 3.403, 3.084, and 4.312 in the 0- < 5 age group to the lowest values of 0.061, 0.063, and 0.071 in the 15- < 20 age group, and subsequently increased to peak values of 131.617, 134.317, and 133.610 in the ≥85 age group, with all P < 0.001. The period effects showed a decline trend, with both incidence and mortality RRs reaching their lowest values in 2017-2021, at 0.521, 0.582, 0.498 and 0.273, 0.283, 0.265, respectively, with all P < 0.001. The cohort effects initially increased and then decreased. The RRs of incidence rose from the lowest values of 0.254, 0.312, and 0.214 in 1907-1911 (all P < 0.001) to peak values of 1.868, 1.493, and 2.142 in 1997-2001 (P < 0.001 for the total population and females, P=0.009 for males), and then decreased to low values of 1.212, 0.873, and 1.352 in 2017-2021 (all P>0.05). The RRs of mortality increased from low values of 0.144, 0.165, and 0.143 in 1907-1911 (all P < 0.001) to peak values of 3.613, 3.265, and 3.584 in 2002-2006 (all P < 0.001), and then decreased to low values of 2.315, 2.054, and 2.313 in 2017-2021 (P=0.011 for the total population, P=0.027 for males, P=0.016 for females). Predictions from the ARIMA model suggested that from 2022 to 2026, the incidence of infectious diarrhea in China is projected to show an upward trend, while mortality is expected to continue declining.

Conclusions

The incidence and mortality of infectious diarrhea in China are influenced by age, period, and cohort effects. While the incidence shows an upward trend, mortality continues to decline. Children and the elderly remain high-risk populations for both onset and death. Targeted prevention strategies should be implemented to reduce the disease burden of infectious diarrhea.

Infectious diarrhea  /  Trends  /  Age-period-cohort model  /  Prediction
王宇皓, 杨亭, 徐洲, 李晖, 韩有, 周东明, 陈琼. 1990—2021年中国感染性腹泻发病与死亡变化趋势分析及预测研究. 中华疾病控制杂志, 2026 , 30 (2) : 143 -152 . DOI: 10.16462/j.cnki.zhjbkz.2026.02.003
Yuhao WANG, Ting YANG, Zhou XU, Hui LI, You HAN, Dongming ZHOU, Qiong CHEN. Analysis and prediction of trends in the incidence and mortality of infectious diarrhea in China from 1990 to 2021[J]. Chinese Journal of Disease Control and Prevention, 2026 , 30 (2) : 143 -152 . DOI: 10.16462/j.cnki.zhjbkz.2026.02.003
感染性腹泻是指肠道感染细菌、病毒、寄生虫等病原体而引起的腹泻,具有流行范围广、发病率高等基本特点[1]。普通人群感染后常有发热、恶心、呕吐、腹痛、腹泻等多种临床症状,病情严重者可因大量丢失水、电解质而引起休克[2]。研究显示,5岁以下儿童及老年人是疾病负担较重的人群[3]。随着我国经济社会的高质量发展,人口流动加快,以及饮食方式的改变等多种因素影响,感染性腹泻仍是重要的公共卫生问题之一[4]。目前关于中国感染性腹泻的流行病学研究主要集中在较小行政区域或短时期内人群的描述性分析[5-6],对于全国范围内疾病的长期变化趋势和预测研究相对较少。本研究对中国感染性腹泻的发病和死亡趋势进行分析和预测, 以期为加强感染性腹泻的监测预警和防控治疗提供参考依据。
研究资料来源于2021年全球疾病负担(Global Burden of Disease, GBD)数据库(http://ghdx.healthdata.org/),该数据库由华盛顿大学下属的健康指标与评估研究中心(Institute for Health Metrics and Evaluation, IHME)开发维护,所有数据向全球研究人员开放使用[4]。本研究利用GBD结果工具对中国感染性腹泻的流行病学数据进行提取, 获得了1990―2021年中国感染性腹泻不同性别、年份、年龄人群的发病率和死亡率。
参考张曼曼等[7]的分析方法,利用Joinpoint回归计算年度变化百分比(annual percent change, APC)和平均年度变化百分比(average annual percent change, AAPC)2个关键指标进行趋势分析。
本研究以连续5年为区间,将1992―2021年划分为6个时期;以连续5岁为间隔划分0~<5岁、5~<10岁…80~<85岁、≥85岁共计18组;按照出生队列=时期-年龄的方法,得到23个出生队列。构建年龄-时期-队列模型,计算偏差、赤池信息准则(Akaike information criterion, AIC)和贝叶斯信息准则(Bayesian information criterion, BIC)。偏差越接近100%、AIC和BIC值越小表明模型的稳健性和可信度越高。分析年龄-时期-队列的发病和死亡RRRR升高表示相关风险增加;RR下降表示相关风险降低。采用R 4.5.1软件构建年龄-时期-队列模型得到的RR反映相对于历史平均水平的风险波动,参照组为隐含的年龄-时期-队列效应平均趋势。
基于ARIMA模型对发病率和死亡率数据进行深度分析,计算平均绝对百分比误差(mean absolute percentage error, MAPE),MAPE越小代表模型拟合效果好,预测精度高,进一步生成时间序列预测区间,直观展示未来疾病发展趋势,辅助风险评估。
采用R 4.5.1软件segmented程序包进行Joinpoint回归分析,mgcv程序包构建年龄-时期-队列模型进行分析,forecast程序包构建ARIMA模型进行预测,并绘制了文中相关图表。检验水准α=0.05。
1990―2021年中国感染性腹泻标准化发病率呈现下降趋势,总人群、男性、女性的发病率分别由1990年的25 458/10万、25 753/10万、25 113/10万降至2021年的5 894/10万、6 520/10万、5 202/10万。不同年份的感染性腹泻发病率男性均高于女性,见图 1A 。Joinpoint回归模型显示,总人群、男性、女性感染性腹泻发病率下降的时间节点均为2000年。1990―2000年感染性腹泻年均发病率下降较慢,APC分别为-2.772%、-2.671%、-2.893%;2000年之后下降加快,APC分别为-6.322%、-5.943%、-6.815%。APC下降趋势均有统计学意义(均P < 0.001)。总人群、男性、女性AAPC分别为-5.223%、-4.905%、-5.656%。
1990―2021年中国感染性腹泻标准化死亡率呈现下降趋势,总人群、男性、女性死亡率分别由1990年的9.323/10万、9.560/10万、9.224/10万降至2021年的0.335/10万、0.373/10万、0.312/10万。除1997―2005年感染性腹泻死亡率女性高于男性外,其余年份男性均高于女性,见图 1B 。Joinpoint回归模型显示,总人群、男性、女性感染性腹泻死亡率下降的时间节点均为2014年。1990―2014年感染性腹泻年均死亡率下降较快,APC分别为-12.342%、-11.913%、-12.734%;2014年之后下降减慢,APC分别为-5.247%、-5.904%、-4.642%。APC下降趋势均有统计学意义(均P < 0.001)。总人群、男性、女性AAPC分别为-10.843%、-10.482%、-11.151%。
本研究构建的年龄-时期-队列发病率模型中总人群、男性、女性偏差分别为97.432%、97.241%、97.345%,AIC值分别为-917、-891、-898,BIC值分别为-809、-783、-790。总人群模型的偏差相对于男性和女性模型更接近100%,AIC值、BIC值低于男性和女性模型,说明整合所有性别数据的模型在平衡拟合优度与复杂度方面表现更优。女性和男性模型的AIC值、BIC值基本相同,表明性别差异对发病率的解释程度有限,进一步提示年龄-时期-队列效应对感染性腹泻发病率的影响占主要地位。
年龄-时期-队列模型分析结果显示,1990―2021年中国感染性腹泻的发病风险随年龄增长呈现先下降后上升的趋势,总人群、男性和女性发病率RR从0~<5岁组的峰值(2.432、3.364、2.002)下降至25~<30岁组的最低值(0.478、0.535、0.451),而后上升至≥85岁组的另一个峰值(3.204、2.523、3.774),均P < 0.001。见表 1图 2A。感染性腹泻发病率的时期效应呈下降趋势,总人群、男性和女性RR分别从1992―1996年的峰值(2.172、1.924、2.372)下降至2017―2021年的最低值(0.521、0.582、0.498),均P < 0.001。见表 1图 2B。感染性腹泻发病率的队列效应呈现先升高后下降趋势,总人群、男性和女性RR分别从1907―1911年的最低值[0.254、0.312、0.214(均P < 0.001)]升高至1997―2001年的峰值[1.868、1.493、2.142(总人群、女性P < 0.001,男性P=0.009)],而后下降至2017―2021年的低值[1.212、0.873、1.352(均P>0.05)]。见表 1图 2C
本研究构建的年龄-时期-队列死亡率模型中总人群、男性、女性偏差分别为99.241%、99.323%、99.132%,AIC值分别为-386、-425、-304,BIC值分别为-287、-325、-205。男性模型偏差相对于总人群和女性模型更接近100%,AIC、BIC值也最低,说明男性死亡率模型在平衡拟合优度与复杂度方面表现最优,模型拟合结果提示男性死亡率数据可能质量更高或变异更小。
年龄-时期-队列模型分析结果显示,1990―2021年中国感染性腹泻的死亡风险随年龄增长呈现先下降后上升的趋势,总人群、男性和女性死亡率RR分别从0~<5岁组的高值(3.403、3.084、4.312)下降至15~<20岁组的最低值(0.061、0.063、0.071),而后上升至≥85岁组的峰值(131.617、134.317、133.610),均P < 0.001。见表 2图 3A。感染性腹泻死亡率的时期效应呈下降趋势,总人群、男性和女性RR分别从1992―1996年的峰值(3.485、3.344、3.576)下降至2017―2021年的最低值(0.273、0.283、0.265),均P < 0.001。见表 2图 3B。感染性腹泻死亡率的队列效应呈现先升高后下降趋势,总人群、男性和女性RR分别从1907―1911年的低值[0.144、0.165、0.143(均P < 0.001)]升高至2002―2006年的峰值[3.613、3.265、3.584(均P < 0.001)],而后下降至2017―2021年的低值[2.315、2.054、2.313(总人群P=0.011,男性P=0.027,女性P=0.016)]。见表 2图 3C
本研究构建的ARIMA发病率模型中总人群、男性、女性MAPE分别为5.872%、5.698%、5.587%,数据近似且值较小,表明不同性别模型拟合效果理想,预测精度高。结果显示,2022―2026年中国感染性腹泻发病率呈上升趋势,预计总人群、男性、女性发病率从2022年的4 922/10万、5 113/10万、4 759/10万升高至2026年的5 421/10万、5 623/10万、5 268/10万。见表 3
ARIMA死亡率模型中总人群、男性、女性MAPE分别为6.334%、6.454%、6.278%,具有相似的拟合结果。预测结果表明,2022―2026年中国感染性腹泻死亡率呈下降趋势,预计总人群、男性、女性死亡率从2022年的8.290/10万、9.680/10万、7.460/10万下降至2026年的0.225/10万、0.257/10万、0.185/10万。见表 3
1990―2021年中国感染性腹泻的总人群、男性、女性发病率和死亡率均呈下降趋势,发病率分别由1990年的25 458/10万、25 753/10万、25 113/10万下降至2021年的5 894/10万、6 520/10万、5 202/10万;死亡率由1990年的9.323/10万、9.560/10万、9.224/10万下降至2021年的0.335/10万、0.373/10万、0.312/10万,与Wu等[8]研究结果相似,这与我国经济快速发展、卫生条件和医疗水平的改善有密切关系。男性感染性腹泻的发病率在不同年份始终高于女性,而死亡率除了在1997―2005年女性高于男性外,其余年份也均为男性高于女性,可能因为男性更多在户外工作和生活、社交范围广且不良卫生习惯多,导致感染风险较高[9]。Joinpoint回归分析显示,总人群、男性、女性感染性腹泻发病率APC均在2000年发生转折,表现为2000年后发病率下降速度较之前年份加快,可能与我国进入新世纪后快速提高城市化率,以及政府施行精准的公共卫生干预措施有关[10];总人群、男性、女性感染性腹泻死亡率APC转折为2014年,表现为2014年后死亡率下降较之前减慢,可能因为中国逐步进入老龄化社会,有基础疾病的中老年群体增多,发病后症状严重,在一定程度上增加了死亡风险[2]
本研究通过年龄-时期-队列模型分析发现,随着年龄的增长,中国感染性腹泻发病和死亡风险呈现先下降后上升的趋势,总人群、男性和女性的发病率和死亡率RR从0~<5岁组开始下降,至15~<30岁组降为最低值,而后上升到≥85岁组为最高值,可能因为5岁以下婴幼儿免疫系统、消化系统功能还不健全,易被诺如病毒、轮状病毒等感染而发生病毒性腹泻[11];青少年自身免疫系统逐步发育成熟,并且大多数时间在学校接受文化教育,养成了良好的卫生习惯,与其他年龄组相比也较少接触各类肠道病原体,因而发病风险降低[12]。但年龄超过30岁后,社会活动增多、在外就餐频繁,感染疾病的风险升高。特别是60岁以上人群免疫系统功能减退,消化能力衰退、机体营养状况变差,且对病原体的抵抗能力减弱、社会医疗资源分配变少,共同导致了发病率升高[13]。值得注意的是,在不同性别人群中,男性在0~<45岁组的感染性腹泻发病风险高于女性,45岁之后变为女性高于男性,可能与女性中老年期免疫功能更脆弱,且在生活中多参与照顾老人和儿童,接触病原体的机会增加有关[12]
时期效应分析显示,总人群、男性、女性的感染性腹泻发病率和死亡率RR均呈现下降趋势,在2017―2021年降为最低值,其原因可能是多方面的:(1)中国持续开展公共卫生服务工作,不断改良厕所和污水处理设备,为人群提供清洁的饮用水[14]。研究表明关键卫生基础设施的改进可以降低感染性腹泻发病和死亡风险[15]。(2)人群疫苗接种率稳步提高,轮状病毒疫苗的推广降低了儿童病毒性腹泻的发病率[16],同时对口服补液溶液和抗生素药物的优化使用也减少了腹泻患者发展为危重症的风险[12]。(3)中国高等教育的发展和健康知识的宣传普及,人群普遍增强了卫生防病意识,改正了不良行为习惯,从而降低了各年龄组人群的感染风险[17]
队列效应分析显示,1907―1911年出生人群的发病和死亡风险最低,之后开始升高到1997―2006年的峰值,而后逐步降至2017―2021年的最低值。可能因为出生年代较早的队列对于腹泻疾病的就诊率低,同时医院的整体医疗水平不高、实验室检测设备精度不足,不能完全识别对应的肠道病原体[18];另外由于中国法定传染病报告体系的完善,使监测数据的质量和完整性得到了提高,在一定程度上增加了发病率和死亡率[11]。在21世纪之后出生的人群,社会整体卫生和健康水平有了长足进步,使队列的发病和死亡风险持续降低。
本研究通过ARIMA模型预测2022―2026年中国感染性腹泻的发病率和死亡率,结果表明,死亡率仍保持下降趋势,但发病率呈现一定的上升趋势。其原因可能为重组诺如病毒的产生和轮状病毒优势血清型发生变化引起腹泻病原谱的增加,导致检出率升高[11]。研究表明,2022年以来中国年平均气温持续高于往年[19],气候变暖同样可以引起致病微生物繁殖传播速度加快[10]。因此,持续监测感染性腹泻的病原谱变化情况,关注特定地区和人群的疾病发展趋势,从而制定不同的干预措施至关重要。
本研究存在的局限性:(1)2021年GBD数据库无法获得中国不同省市和季节的发病和死亡相关数据,因此未能进行多因素综合分析;(2)构建的分析和预测模型基于公开数据,可能因为数据的不完善或准确性不足而影响结果。
综上所述,1990―2021年中国感染性腹泻的发病率和死亡率均呈下降趋势,2022―2026年发病率呈现上升趋势,儿童和老年人是发病和死亡风险较高的人群。今后,应继续加强公共卫生监测和健康干预,精准防控,保护易感人群,以减少感染性腹泻的发生。
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2026年第30卷第2期
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doi: 10.16462/j.cnki.zhjbkz.2026.02.003
  • 接收时间:2025-08-20
  • 首发时间:2026-05-08
  • 出版时间:2026-02-10
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  • 收稿日期:2025-08-20
  • 修回日期:2025-12-03
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    东部战区疾病预防控制中心,南京 210002

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2种不同金属材料的力学参数

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

Genus
种数
Number of
species
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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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