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Article(id=1241522766655050475, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241522764012647140, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202306479, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1687536000000, receivedDateStr=2023-06-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773931693947, onlineDateStr=2026-03-19, pubDate=1704816000000, pubDateStr=2024-01-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773931693947, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773931693947, creator=13701087609, updateTime=1773931693947, updator=13701087609, issue=Issue{id=1241522764012647140, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='1', pageStart='1', pageEnd='192', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773931693318, creator=13701087609, updateTime=1773931808852, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241523248643494379, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241522764012647140, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241523248643494380, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241522764012647140, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=15, endPage=20, ext={EN=ArticleExt(id=1241522767389053685, articleId=1241522766655050475, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Incidence and mortality trend of stroke in China from 2005 to 2019 and its forecast in the next decade, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the incidence and mortality trend of stroke in Chinese population from 2005 to 2019, and to predict the incidence and death from 2020 to 2029.

Methods

The incidence and mortality data of stroke in Chinese population according to global burden of disease (GBD) were used. Joinpoint regression analysis was used to analyze the changing trend of stroke incidence and mortality in the population, and the annual change percentage and average annual change percentage and their 95% confidence interval were calculated. The GM（1，1）model was established by R, and the incidence and mortality of stroke in China from 2020 to 2029 were predicted.

Results

The incidence of stroke in China showed an upward trend from 2005 to 2019. The incidence of stroke in men increased from 197.94/100 000 in 2005 to 269.17/100 000 in 2019, with an average annual increase of 2.196% and the fastest increase during 2010 and 2014. The stroke incidence in women rose from 198.57/100 000 in 2005 to 284.46/100 000 in 2019, with an average annual increase of 2.616% and the fastest increase during 2017 and 2019. The male mortality rate showed a slight upward trend. It was predicted that in 2029, the incidence of stroke in China may reach 340.93/100 000 for males and 376.67/100 000 for females, and the mortality rate may reach 191.44/100 000 for males and 126.52/100 000 for females.

Conclusion

The study shows that the incidence of stroke is on the rise in China, and the incidence of stroke in females is higher than that in males. The mortality rate of stroke is on the rise in males. Male and female incidence and male mortality may continue to rise from 2020 to 2029, and stroke prevention and control still need to be strengthened.

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目的

分析中国人群2005—2019年脑卒中发病与死亡趋势，预测2020—2029年发病和死亡情况。

方法

利用GBD中国人群脑卒中发病和死亡数据。采用Joinpoint连接点回归分析法分析人群脑卒中发病率和死亡率变化趋势；计算年度变化百分比和平均年度变化百分比及其95%置信区间。应用R建立GM（1，1）模型，并预测2020—2029年中国脑卒中的发病和死亡情况。

结果

2005—2019年中国脑卒中发病率呈上升趋势，男性从2005年的197.94/10万上升到2019年的269.17/10万，平均每年上升2.196%，上升速度最快的是2010—2014年。女性从2005年的198.57/10万上升到2019年的284.46/10万，平均每年上升2.616%，上升速度最快的是2017—2019年。男性死亡率略呈上升趋势。预测表明，2029年中国脑卒中男性发病率将可能达到340.93/10万、女性376.67/10万；男性死亡率将可能达到191.44/10万、女性126.52/10万。

结论

研究显示中国脑卒中发病呈上升趋势，女性发病率整体高于男性。脑卒中死亡男性呈上升趋势。2020—2029年男性和女性发病、男性死亡可能持续上升，脑卒中的防控仍需加强。

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让蔚清，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=c+JCS8azQM/nn+a4aLAKgQ==, magXml=2NYXxdEIKZexVEI6ZFf/SQ==, pdfUrl=null, pdf=m4B/Of4MGsEb4FPMjomb+A==, pdfFileSize=744490, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=9d5zti9XCFQzWVCpCbz/Uw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=vOUUVu3dAlP4Yv/OSld0Qg==, mapNumber=null, authorCompany=null, fund=null, authors=

熊文婧（1990—），女，硕士，主治医师，研究方向：疾病流行规律及中医防治

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2.南华大学附属第一医院，湖南 衡阳 421000, bio={"content":"

熊文婧（1990—），女，硕士，主治医师，研究方向：疾病流行规律及中医防治

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熊文婧（1990—），女，硕士，主治医师，研究方向：疾病流行规律及中医防治

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Advances in nutritional support therapy for stroke prevention and treatment[J]. 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The changing trend of stroke incidence in China from 2005 to 2019 (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
时期（年）男性女性
APC(95%CI)t值P值APC(95%CI)t值P值
2005—20100.752*(0.465～1.040)7.729 60.0021.943*(1.797～2.088)37.346≤0.001
2010—20143.593*(2.970～4.219)16.252<0.0013.152*(2.845～3.460)28.926≤0.001
2014—20172.046*(0.894～3.211)4.9530.0082.230*(1.656～2.806)10.889≤0.001
2017—20193.285*(2.169～4.413)8.2610.0013.822*(3.269～4.378)19.501≤0.001
), ArticleFig(id=1241677626385952883, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表1, caption=

2005—2019年中国脑卒中患者发病率变化趋势分析(%)

, figureFileSmall=null, figureFileBig=null, tableContent=
时期（年）男性女性
APC(95%CI)t值P值APC(95%CI)t值P值
2005—20100.752*(0.465～1.040)7.729 60.0021.943*(1.797～2.088)37.346≤0.001
2010—20143.593*(2.970～4.219)16.252<0.0013.152*(2.845～3.460)28.926≤0.001
2014—20172.046*(0.894～3.211)4.9530.0082.230*(1.656～2.806)10.889≤0.001
2017—20193.285*(2.169～4.413)8.2610.0013.822*(3.269～4.378)19.501≤0.001
), ArticleFig(id=1241677626474033269, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=EN, label=Table 2, caption=

The average annual percent change (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
队列范围起点（年）终点（年）AAPC(95%CI)t#值P值
男性-3 Joinpoints全距200520192.196*（1.942～2.449）17.141≤0.001
女性-3 Joinpoints全距200520192.616*（2.490～2.742）41.263≤0.001
), ArticleFig(id=1241677626583085180, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表2, caption=

平均年度变化百分比（%）

, figureFileSmall=null, figureFileBig=null, tableContent=
队列范围起点（年）终点（年）AAPC(95%CI)t#值P值
男性-3 Joinpoints全距200520192.196*（1.942～2.449）17.141≤0.001
女性-3 Joinpoints全距200520192.616*（2.490～2.742）41.263≤0.001
), ArticleFig(id=1241677626687942785, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=EN, label=Table 3, caption=

Trend analysis of mortality rate changes in stroke patients in China from 2005 to 2019 (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
时期（年）男性女性
APC(95%CI)t值P值APC(95%CI)t值P值
2005—2007-2.113(-4.295～0.120)-2.6290.058-2.991(-6.051～0.170)-2.6290.058
2007—20102.823*(0.556～5.141)3.4670.0260.710(-2.504～4.029)0.6050.578
2010—20170.472*(0.110～0.837)3.6160.022-1.211*(-2.215～-0.196)-3.3100.030
2017—20191.614(-0.478～3.749)2.1370.0992.237*(-1.222～3.262)6.1560.004
), ArticleFig(id=1241677626868297864, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表3, caption=

2005—2019年中国脑卒中患者死亡率变化趋势分析(%)

, figureFileSmall=null, figureFileBig=null, tableContent=
时期（年）男性女性
APC(95%CI)t值P值APC(95%CI)t值P值
2005—2007-2.113(-4.295～0.120)-2.6290.058-2.991(-6.051～0.170)-2.6290.058
2007—20102.823*(0.556～5.141)3.4670.0260.710(-2.504～4.029)0.6050.578
2010—20170.472*(0.110～0.837)3.6160.022-1.211*(-2.215～-0.196)-3.3100.030
2017—20191.614(-0.478～3.749)2.1370.0992.237*(-1.222～3.262)6.1560.004
), ArticleFig(id=1241677627073818768, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=EN, label=Table 4, caption=

The average annual percent change (%)

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队列范围起点（年）终点（年）AAPC(95%CI)t#值P#值
男性-3 Joinpoints全距200520190.759*（0.281～1.239）3.1180.002
女性-3 Joinpoints全距20052019-0.085*（-0.755～0.589）-0.2480.804
), ArticleFig(id=1241677627266756758, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表4, caption=

平均年度变化百分比（%）

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队列范围起点（年）终点（年）AAPC(95%CI)t#值P#值
男性-3 Joinpoints全距200520190.759*（0.281～1.239）3.1180.002
女性-3 Joinpoints全距20052019-0.085*（-0.755～0.589）-0.2480.804
), ArticleFig(id=1241677627384197273, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=EN, label=Table 5, caption=

Analysis of the GM (1,1) model of incidence rate of stroke in different genders in China from 2005 to 2019 (1/100 000)

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）男性女性
x0（t）x1（t） 相对误差（%）x0（t）x1（t） 相对误差 (%)
2005197.94197.94197.940.000198.57198.57198.570.000
2006200.77390.70192.76-3.989201.82396.94198.37-1.706
2007201.91588.30197.60-2.132205.33600.69203.74-0.770
2008202.31790.86202.560.126209.19809.96209.260.033
2009203.70998.50207.641.938213.731 024.88214.930.563
2010207.101 211.36212.862.779218.741 245.63220.750.918
2011213.341 429.56218.202.278224.971 472.36226.750.779
2012220.701 653.24223.681.348231.761 705.23232.870.476
2013228.571 882.53229.290.319238.961 944.40239.170.088
2014236.762 117.58235.05-0.722246.502 190.04245.65-0.345
2015243.642 358.53240.95-1.103253.262 442.34252.300.380
2016247.302 605.53247.00-0.123257.952 701.47259.130.458
2017251.692 858.73253.200.597263.612 967.62266.150.962
2018260.023 118.28259.55-0.178273.333 240.98273.350.009
2019269.175 443.54266.07-1.151284.463 521.73280.76-1.303
), ArticleFig(id=1241677627526803613, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表5, caption=

2005—2019年中国不同性别脑卒中发病率GM(1,1)模型分析（1/10万）

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）男性女性
x0（t）x1（t） 相对误差（%）x0（t）x1（t） 相对误差 (%)
2005197.94197.94197.940.000198.57198.57198.570.000
2006200.77390.70192.76-3.989201.82396.94198.37-1.706
2007201.91588.30197.60-2.132205.33600.69203.74-0.770
2008202.31790.86202.560.126209.19809.96209.260.033
2009203.70998.50207.641.938213.731 024.88214.930.563
2010207.101 211.36212.862.779218.741 245.63220.750.918
2011213.341 429.56218.202.278224.971 472.36226.750.779
2012220.701 653.24223.681.348231.761 705.23232.870.476
2013228.571 882.53229.290.319238.961 944.40239.170.088
2014236.762 117.58235.05-0.722246.502 190.04245.65-0.345
2015243.642 358.53240.95-1.103253.262 442.34252.300.380
2016247.302 605.53247.00-0.123257.952 701.47259.130.458
2017251.692 858.73253.200.597263.612 967.62266.150.962
2018260.023 118.28259.55-0.178273.333 240.98273.350.009
2019269.175 443.54266.07-1.151284.463 521.73280.76-1.303
), ArticleFig(id=1241677627656827045, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=EN, label=Table 6, caption=

Fitting analysis of GM (1,1) model for incidence rate of stroke in China

, figureFileSmall=null, figureFileBig=null, tableContent=
预测指标a值u值检验统计量CP值模型等级
男性-0.025185.4750.3420.953一级
女性-0.027190.4310.0671.000一级
), ArticleFig(id=1241677627757490342, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表6, caption=

中国脑卒中发病率GM(1,1)模型拟合分析

, figureFileSmall=null, figureFileBig=null, tableContent=
预测指标a值u值检验统计量CP值模型等级
男性-0.025185.4750.3420.953一级
女性-0.027190.4310.0671.000一级
), ArticleFig(id=1241677627853959339, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=EN, label=Table 7, caption=

GM (1,1) model predicted values （1/100 000）

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）发病率死亡率
男性女性男性女性
2020272.75296.16175.23126.76
2021279.60304.19176.95126.73
2022286.61312.42178.70126.70
2023293.81320.88180.40126.68
2024301.18329.57182.25126.65
2025308.74338.50184.05126.62
2026316.49347.66185.87126.60
2027324.44357.08187.71126.57
2028332.58366.74189.56126.54
2029340.93376.67191.44126.52
), ArticleFig(id=1241677627967205555, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表7, caption=

GM (1,1)模型预测值（1/10万）

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）发病率死亡率
男性女性男性女性
2020272.75296.16175.23126.76
2021279.60304.19176.95126.73
2022286.61312.42178.70126.70
2023293.81320.88180.40126.68
2024301.18329.57182.25126.65
2025308.74338.50184.05126.62
2026316.49347.66185.87126.60
2027324.44357.08187.71126.57
2028332.58366.74189.56126.54
2029340.93376.67191.44126.52
), ArticleFig(id=1241677628067868853, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=EN, label=Table 8, caption=

Analysis of the GM (1,1) model for stroke mortality of different genders in China from 2005 to 2019 (1/100 000)

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）男性女性
x0（t）x1（t） 相对误差(%)x0（t）x1（t） 相对误差(%)
2005156.89156.89156.890.000134.53134.53134.530.000
2006151.23309.57152.680.957129.92264.27129.74-0.141
2007150.48463.76154.192.463127.06393.24128.981.511
2008153.65619.47155.711.342126.81521.47128.231.118
2009158.08776.72157.25-0.527127.89648.95127.48-0.324
2010162.47935.53158.81-2.254129.25775.68126.73-1.947
2011163.881 095.90160.37-2.142129.18901.68126.00-2.467
2012164.821 257.86161.96-1.736124.79026.94125.260.375
2013164.551 421.42163.56-0.603123.641 151.47124.530.717
2014164.871 586.60165.180.189123.161 275.27123.800.523
2015165.591 753.41166.810.736122.121 398.35123.080.079
2016168.281 921.87168.460.109124.371 520.71122.36-0.017
2017168.662 091.00170.120.870126.721 642.36121.65-0.040
2018169.852 263.80171.811.149129.551 763.30120.94-0.664
2019173.992 437.31173.50-0.279133.051 883.53120.23-0.979
), ArticleFig(id=1241677628206280889, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表8, caption=

2005—2019年中国不同性别脑卒中死亡率GM(1,1)模型分析（1/10万）

, figureFileSmall=null, figureFileBig=null, tableContent=
年份（年）男性女性
x0（t）x1（t） 相对误差(%)x0（t）x1（t） 相对误差(%)
2005156.89156.89156.890.000134.53134.53134.530.000
2006151.23309.57152.680.957129.92264.27129.74-0.141
2007150.48463.76154.192.463127.06393.24128.981.511
2008153.65619.47155.711.342126.81521.47128.231.118
2009158.08776.72157.25-0.527127.89648.95127.48-0.324
2010162.47935.53158.81-2.254129.25775.68126.73-1.947
2011163.881 095.90160.37-2.142129.18901.68126.00-2.467
2012164.821 257.86161.96-1.736124.79026.94125.260.375
2013164.551 421.42163.56-0.603123.641 151.47124.530.717
2014164.871 586.60165.180.189123.161 275.27123.800.523
2015165.591 753.41166.810.736122.121 398.35123.080.079
2016168.281 921.87168.460.109124.371 520.71122.36-0.017
2017168.662 091.00170.120.870126.721 642.36121.65-0.040
2018169.852 263.80171.811.149129.551 763.30120.94-0.664
2019173.992 437.31173.50-0.279133.051 883.53120.23-0.979
), ArticleFig(id=1241677628340498621, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=EN, label=Table 9, caption=

Fitting analysis of the GM (1,1) model for stroke mortality in China

, figureFileSmall=null, figureFileBig=null, tableContent=
预测指标a值u值检验统计量CP值模型等级
男性0.006130.9030.1361.000一级
女性-0.001150.3860.2301.000一级
), ArticleFig(id=1241677629846253762, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241522766655050475, language=CN, label=表9, caption=

中国脑卒中死亡率GM(1,1)模型拟合分析

, figureFileSmall=null, figureFileBig=null, tableContent=
预测指标a值u值检验统计量CP值模型等级
男性0.006130.9030.1361.000一级
女性-0.001150.3860.2301.000一级
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2005—2019年中国脑卒中发病与死亡趋势及未来十年预测
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熊文婧 1, 2 , 徐杰茹 1 , 张敏 1 , 姚承志 1 , 赵湘铃 1 , 吴霞 1 , 让蔚清 1
现代预防医学 | 流行病与统计方法 2024,51(1): 15-20
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现代预防医学 | 流行病与统计方法 2024, 51(1): 15-20
2005—2019年中国脑卒中发病与死亡趋势及未来十年预测
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熊文婧1, 2, 徐杰茹1, 张敏1, 姚承志1, 赵湘铃1, 吴霞1, 让蔚清1
作者信息
  • 1.南华大学公共卫生学院，湖南 衡阳 421001
  • 2.南华大学附属第一医院，湖南 衡阳 421000

    • 熊文婧（1990—），女，硕士，主治医师，研究方向：疾病流行规律及中医防治

通讯作者:

让蔚清，E-mail:
Incidence and mortality trend of stroke in China from 2005 to 2019 and its forecast in the next decade
Wen-jing XIONG1, 2, Jie-ru XU1, Min ZHANG1, Cheng-zhi YAO1, Xiang-ling ZHAO1, Xia WU1, Wei-qing RANG1
Affiliations
  • School of Public Health, Nanhua University, Hengyang, Hunan 421001, China
出版时间: 2024-01-10 doi: 10.20043/j.cnki.MPM.202306479
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摘要
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目的

分析中国人群2005—2019年脑卒中发病与死亡趋势，预测2020—2029年发病和死亡情况。

方法

利用GBD中国人群脑卒中发病和死亡数据。采用Joinpoint连接点回归分析法分析人群脑卒中发病率和死亡率变化趋势；计算年度变化百分比和平均年度变化百分比及其95%置信区间。应用R建立GM（1，1）模型，并预测2020—2029年中国脑卒中的发病和死亡情况。

结果

2005—2019年中国脑卒中发病率呈上升趋势，男性从2005年的197.94/10万上升到2019年的269.17/10万，平均每年上升2.196%，上升速度最快的是2010—2014年。女性从2005年的198.57/10万上升到2019年的284.46/10万，平均每年上升2.616%，上升速度最快的是2017—2019年。男性死亡率略呈上升趋势。预测表明，2029年中国脑卒中男性发病率将可能达到340.93/10万、女性376.67/10万；男性死亡率将可能达到191.44/10万、女性126.52/10万。

结论

研究显示中国脑卒中发病呈上升趋势，女性发病率整体高于男性。脑卒中死亡男性呈上升趋势。2020—2029年男性和女性发病、男性死亡可能持续上升，脑卒中的防控仍需加强。

脑卒中  /  发病趋势  /  死亡趋势  /  GM（1，1）模型  /  预测
Objective

To analyze the incidence and mortality trend of stroke in Chinese population from 2005 to 2019, and to predict the incidence and death from 2020 to 2029.

Methods

The incidence and mortality data of stroke in Chinese population according to global burden of disease (GBD) were used. Joinpoint regression analysis was used to analyze the changing trend of stroke incidence and mortality in the population, and the annual change percentage and average annual change percentage and their 95% confidence interval were calculated. The GM（1，1）model was established by R, and the incidence and mortality of stroke in China from 2020 to 2029 were predicted.

Results

The incidence of stroke in China showed an upward trend from 2005 to 2019. The incidence of stroke in men increased from 197.94/100 000 in 2005 to 269.17/100 000 in 2019, with an average annual increase of 2.196% and the fastest increase during 2010 and 2014. The stroke incidence in women rose from 198.57/100 000 in 2005 to 284.46/100 000 in 2019, with an average annual increase of 2.616% and the fastest increase during 2017 and 2019. The male mortality rate showed a slight upward trend. It was predicted that in 2029, the incidence of stroke in China may reach 340.93/100 000 for males and 376.67/100 000 for females, and the mortality rate may reach 191.44/100 000 for males and 126.52/100 000 for females.

Conclusion

The study shows that the incidence of stroke is on the rise in China, and the incidence of stroke in females is higher than that in males. The mortality rate of stroke is on the rise in males. Male and female incidence and male mortality may continue to rise from 2020 to 2029, and stroke prevention and control still need to be strengthened.

Stroke  /  Incidence trend  /  Mortality trend  /  GM （1,1）model  /  Prediction
熊文婧, 徐杰茹, 张敏, 姚承志, 赵湘铃, 吴霞, 让蔚清. 2005—2019年中国脑卒中发病与死亡趋势及未来十年预测. 现代预防医学, 2024 , 51 (1) : 15 -20 . DOI: 10.20043/j.cnki.MPM.202306479
Wen-jing XIONG, Jie-ru XU, Min ZHANG, Cheng-zhi YAO, Xiang-ling ZHAO, Xia WU, Wei-qing RANG. Incidence and mortality trend of stroke in China from 2005 to 2019 and its forecast in the next decade[J]. Modern Preventive Medicine, 2024 , 51 (1) : 15 -20 . DOI: 10.20043/j.cnki.MPM.202306479
正文
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脑卒中又称脑血管意外（cerebralvascular accident），是由于脑部血管突然破裂或因血管阻塞导致血液不能流入大脑而引起脑组织损伤或功能障碍的一组急性脑血管疾病[1]。脑卒中是导致人类死亡和残疾的主要原因之一，严重的威胁着人类生命与健康[2-3]。且由于人口老龄化、风险因素（如高血压）的持续高流行率和管理不足，中国人群脑卒中的发病率与死亡率逐渐上升，我国脑卒中发病人群中年龄<70岁的患者比例持续增加，逐步呈年轻化的趋势[4-5]。
基于一定的数据，分析与预测未来发病和死亡的趋势，对于研究防控对策具有十分重要的意义。本文通过收集2005—2019年中国脑卒中的发病和死亡数据，分析人群脑卒中发病率和死亡率变化趋势；并预测未来十年脑卒中的发病率和死亡率，为相关部门制定预防与控制措施提供依据。
1　资料与方法
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1.1　数据来源
2005—2019年中国脑卒中发病和死亡数据主要来源于全球健康数据交换数据库GHDx，该数据库是由全球疾病负担研究GBD（Global Burden of Disease study，GBD，官方网址http://ghdx.healthdata.org/gbd-results-tool）项目所提供，当前GBD数据库整合了2005—2019年共30年的疾病数据并免费开放[6]。该数据库所收录的中国人群数据是由中国疾病控制中心与美国华盛顿大学健康测量和评价研究院长期合作的结果，地域范围包括了：中国大陆31个省份直辖市和自治区、香港和澳门两个特别行政区；数据依托于全国疾病监测系统、中国疾病预防控制中心的全国死因报告系统、癌症登记处以及孕产妇和儿童监测系统等，可以最大程度保证数据的可靠性和代表性[7]，本研究从GBD数据库中提取2005—2019年中国脑卒中粗发病率和粗死亡率数据进行研究，数据的下载方法参照相关文献[8-9]。
1.2　研究方法
1.2.1　趋势分析
根据《国际疾病分类》（第10版）编码原则，从GHDx数据库中提取2005—2019年中国脑卒中发病与死亡的粗率（脑卒中疾病的国际疾病ICD-10分类编号，stroke：I64；intracerebral hemorrhage：I61；Ischemic stroke: I63.9；Subarachnoid hemorrhage: I60；ICD-10分类号参见https://icd.who.int/browse10/2019/en），并利用Excel 2019摘录中国不同性别人群脑卒中发病和死亡数据。
采用Joinpoint连接点回归分析法分别对人群脑卒中发病率和死亡率进行分析。计算年度变化百分比（annual percentchange，APC）和平均年度变化百分比（average annualpercent change，AAPC）及其95%置信区间（confidence interval，CI）；通过置换检验确定连接点个数及各连接点位置，并检验总体趋势和各时间分段趋势是否有统计学意义，检验水准α=0.05。AAPC<0表示发病率和死亡率逐年下降，AAPC>0表示发病率和死亡率逐年上升，双侧检验，检验水准为α=0.05，AAPC可信区间包含0，表示发病率和死亡率趋于平稳[10]。计算公式参见文献[11-12]。
1.2.2　GM（1,1）预测模型建立及评价
应用R（4.2.0版本）建立GM（1,1）模型[12]，GM(1,1)模型的核心体系即灰色模型(grey model，简称GM )是一种通过累积生成(或用其他方法生成)原始数据得到近似指数规律并建模的方法。灰色预测模型针对不同的问题采用不同的模型，GM (1,1 )模型主要解决生成序列具有指数变化规律，只能描述单调的变化过程。
GM (1,1 )模型的建立参见文献[11-16]：预测模型精度检验参见文献[11,15-17]。若满足C≤0.35且P≥0.95，则可以认为GM (1, 1)预测精度等级高。
2　结果
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2.1　脑卒中发病率趋势分析
2005—2019年我国男女性脑卒中的发病率均成上升趋势，女性的发病率整体高于男性。男性发病率平均每年上升2.196%，从2005年的197.94/10万上升到2019年的269.17/10万，其中上升速度最快的是2010—2014年，APC=3.593%。女性发病率平均每年上升2.616%，从2005年的198.57/10万上升到2019年的284.46/10万，其中上升速度最快的是2017—2019年，APC=3.822%。见图1，表1、2。
2.2　脑卒中死亡率趋势分析
2005—2019年我国男性脑卒中死亡率呈上升趋势，女性的死亡率整体呈平稳趋势。男性死亡率平均每年上升0.759%，从2005年的156.89/10万上升到2019年的173.99/10万，其中上升速度最快的是2007—2010年，APC=2.823%。女性死亡率2005—2007年、2010—2015年间呈下降趋势，APC分别为-2.991%、-1.211%，2015—2019年间呈上升趋势，APC为2.237%。见图2，表3、4。
2.3　2020—2029年脑卒中发病率和死亡率预测
2.3.1　发病趋势
利用2005—2019年中国脑卒中发病数据建立灰色模型，结果显示：男性发病率模型的相对误差的绝对值在0.123% ～3.989 %之间，平均相对误差为1.342 %，预测精度为98.66%。女性发病率模型的相对误差在0.009%～1.706%之间，平均相对误差为0.628%，预测精度为99.37%。男性与女性发病率所建立的GM(1,1)发病率模型的等级均为1级。见表5、6。
通过GM (1,1)模型拟合优度分析，对2020—2029脑卒中的发病率进行预测，预测结果显示，未来十年我国脑卒中发病率保持持续上升趋势，2029年发病率将可能达到男性340.93/10万、女性376.67/10万。见表7。
2.3.2　死亡趋势
利用2005—2019年中国脑卒中死亡数据建立灰色模型，结果显示：男性死亡率模型的相对误差的绝对值在0.109% ～2.463 %之间，平均相对误差为1.097 %，预测精度为98.90%。女性死亡率模型的相对误差在0.017%～2.467%之间，平均相对误差为0.779%，预测精度为99.22%。男性与女性死亡率所建立的GM(1,1)死亡率模型的等级均为1级。见表8、9。
通过GM (1,1)模型拟合优度分析，对我国2020—2029年脑卒中死亡率进行预测，预测结果显示，未来十年我国脑卒中死亡率呈保持持续上升趋势，2029年死亡率将可能达到男性191.44/10万、女性126.52/10万。见表7。
3　讨论
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脑卒中是严重危害国民健康的重大慢性非传染性疾病，具有高发病率、高致残率、高死亡率、高复发率、高经济负担五大特点[18]。全球疾病负担研究(GBD)数据显示，脑卒中是我国成人致死、致残的首位病因，现患人数高居世界首位。
本研究分析发现2005—2019年我国男女性脑卒中的发病率均成上升趋势，女性的发病率整体高于男性。2005—2019年我国男性脑卒中死亡率呈上升趋势，女性脑卒中死亡率整体呈平稳趋势。可能原因：（1）人口老龄化，部分地区的高盐、高糖、高脂饮食或饮酒生活方式等原因，导致脑卒中发生率增加[4,19]；（2）重大公共卫生服务项目支持各地开展心血管疾病、脑卒中等慢性病早诊早治项目，医疗救治技术进步和急救医疗体系的完善，基本保证死亡率呈平稳或下降趋势。
疾病发病与死亡预测不仅有利于研究卫生策略、调整防控方案，还有利于诊疗技术研发。GM(1,1)模型是灰色系统理论中应用最广泛的一种灰色动态预测模型，自1982年以来就得到广泛应用[20-21]。本研究建立GM(1, 1)模型预测2020—2029年脑卒中发病趋势和死亡趋势，结果显示C≤0.35且P≥0.95，预测精度等级均为1级，且按照a值标准判断该模型适合中长期预测。从2020—2029年，我国男女性发病率趋势呈上升趋势；男性死亡率趋势呈上升趋势，女性死亡率趋势则几乎持平，甚至略有下降趋势。糖尿病、血同型半胱氨酸、大型血小板比例是影响脑卒中发病的独立危险因素[19]。HIV感染者/AIDS患者的缺血性卒中发病率呈上升趋势[22]。体力活动者患脑卒中的风险可能更低[23]；脑血管功能积分值降低是脑卒中首发的重要原因[24]。入院时低白蛋白血症的中风患者可能发生感染并发症的风险增加，死亡率高，功能预后差[25]；营养支持可能降低脑卒中死亡[26]。以上研究提示提高健康素养、加强高危人群管理、适当运动、合理营养、定期评估脑血管功能，积极预防糖尿病、高血压、肥胖等疾病，或可有效预防脑卒中发生或降低死亡率。
本研究还存在一些局限性：（1）2020—2029年脑卒中的发病率和死亡率是基于模型预测的结果，随着健康中国行计划的实施、医疗技术水平的提高、健康教育普及等获将提高居民认知和自我防控水平，推测未来疾病发生和死亡实际结果可能会较预测结果偏低；（2）未来在建模技术和数据的进一步完善，预测结果可能也会受到影响；（3）虽然GM(1, 1)模型精度等级高，但在实际生活中脑卒中的发病率和死亡率受诸多因素的影响，需要分别分析影响因素或干预因素，应谨慎对待该预测结果。
基金
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  • 2019年度湖南省芙蓉教学名师专项基金(201RFS001)
  • 2023年南华大学立项课题(230XJZ008)
文献
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2024年第51卷第1期
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doi: 10.20043/j.cnki.MPM.202306479
  • 接收时间：2023-06-24
  • 首发时间：2026-03-19
  • 出版时间：2024-01-10
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  • 收稿日期：2023-06-24
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2019年度湖南省芙蓉教学名师专项基金(201RFS001)
2023年南华大学立项课题(230XJZ008)
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    1.南华大学公共卫生学院，湖南 衡阳 421001
    2.南华大学附属第一医院，湖南 衡阳 421000

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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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