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Article(id=1240375272587980822, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240375270163673092, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202401359, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1705852800000, receivedDateStr=2024-01-22, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773658110042, onlineDateStr=2026-03-16, pubDate=1713974400000, pubDateStr=2024-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773658110042, onlineIssueDateStr=2026-03-16, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773658110042, creator=13701087609, updateTime=1773658110042, updator=13701087609, issue=Issue{id=1240375270163673092, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='8', pageStart='1345', pageEnd='1536', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773658109465, creator=13701087609, updateTime=1773658579758, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240377242795176417, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240375270163673092, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240377242795176418, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240375270163673092, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1377, endPage=1383, ext={EN=ArticleExt(id=1240375273657528349, articleId=1240375272587980822, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Trends and predictions of the burden of three types of injury diseases, China, 1990-2019, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the change of disease burden of injury in China from 1990 to 2019, and to predict the change trend from 2020 to 2034, so as to provide basis for the formulation of injury prevention and control strategies.

Methods

Using the global disease burden research database in 2019, the change trends of age-standardized incidence, prevalence, mortality and disability-adjusted life expectancy rate of injuries in China were analyzed, and the average annual change percentage was calculated.The grey prediction model GM (1) was used to predict the annual DALY change trend from 2020 to 2034.

Results

From 1990 to 2019, the incidence, prevalence, mortality and Daly rate of self-injury and interpersonal violence showed a downward trend, with the largest decrease among people aged 0-9 (AAPC=-2.27%,-0.26%,-4.72%,-6.00%). The incidence and prevalence of traffic injuries showed an upward trend, while mortality and DALY rates generally showed a downward trend, but those over 70 years old showed an upward trend (AAPC=0.26%, 0.88%). The incidence of accidental injuries showed an overall downward trend (AAPC=-0.08%), but showed an upward trend in 2006—2019 (AAPC=2.69%), and the mortality and DALY rates showed an overall downward trend, among which the morbidity, prevalence, mortality and Daly rates of people ≥ 70 years old showed an upward trend (AAPC=1.84%, 1.15%, 0.66%, 0.51%). The grey prediction model showed that the DALY of the three kinds of injuries will show a downward trend from 2020 to 2034. It is estimated that by 2035, the Daly rate will decrease to 166.304 / 100 000, 862.338 / 100 000 and 715.27 / 100 000 respectively.

Conclusion

The mortality rate and DALY rate of three kinds of injuries in China show a general downward trend from 1990 to 2019, but the incidence rate of traffic injuries and accidental injuries are still rising, and the disease burden of the elderly is still increasing.

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目的

分析1990—2019年我国伤害的疾病负担变化，并预测2020—2034年的变化趋势，为制定伤害防控策略提供依据。

方法

利用2019年全球疾病负担研究数据库，分析中国伤害的年龄标准化发病率、患病率、死亡率及伤残调整寿命年率的变化趋势，计算平均年度变化百分比；采用灰色预测模型GM（1,1）预测2020—2034年的DALY变化趋势。

结果

1990—2019年，自我伤害和人际暴力的发病率、患病率、死亡率和DALY率均呈下降趋势，其中以0~9岁人群的降幅最大（AAPC=-2.27%、-0.26%、-4.72%、-6.00%）；交通伤害的发病率和患病率呈上升趋势，死亡率和DALY率总体呈下降趋势，但≥70岁人群呈上升趋势（AAPC=0.26%、0.88%）；意外伤害的发病率总体呈下降趋势（AAPC=-0.08%），但在2006—2019年却呈上升趋势（AAPC=2.69%），死亡率和DALY率总体呈下降趋势，其中≥70岁人群的发病率、患病率、死亡率和DALY率均呈上升趋势（AAPC=1.84%、1.15%、0.66%、0.51%）。灰色预测模型显示，2020—2034年三种伤害的DALY将呈下降趋势，预计到2035年，DALY率分别降至166.304/10万、862.338/10万和715.27/10万。

结论

1990—2019年我国三种伤害的死亡率和DALY率总体呈下降趋势，但交通伤害和意外伤害的发病率仍在上升，老年人的疾病负担仍在加重。

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张态，E-mail：
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宋源龙（1995—），男，硕士在读，研究方向：慢病流行病

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宋源龙（1995—），男，硕士在读，研究方向：慢病流行病

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Chinese Journal of Rehabilitation, 2018, 33(3): 246-248., articleTitle=The present situation and Countermeasures of fall research on the elderly in China, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1240748858800657085, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, xref=null, ext=[AuthorCompanyExt(id=1240748858813239997, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, companyId=1240748858800657085, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Public Health, Dali University, Dali, Yunnan 671000, China), AuthorCompanyExt(id=1240748858821628606, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, companyId=1240748858800657085, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=大理大学公共卫生学院，云南 大理 671000)])], figs=[ArticleFig(id=1240748861682144173, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=EN, label=Fig.1, caption=Change trend of disease burden of injury in Chinese population from 1990 to 2019, figureFileSmall=w9X0qwY5eR19CTGLS5XjBA==, figureFileBig=pgS+6G6qsUb9aQy4FZzhjA==, tableContent=null), ArticleFig(id=1240748861740864438, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=CN, label=图1, caption=1990—2019年中国人群伤害的疾病负担变化趋势

注：A为1990—2019年我国伤害发病率变化趋势；B为1990—2019年我国伤害患病率变化趋势；C为1990—2019年我国伤害死亡率变化趋势；D为1990—2019年我国伤害DALY率变化趋势。

, figureFileSmall=w9X0qwY5eR19CTGLS5XjBA==, figureFileBig=pgS+6G6qsUb9aQy4FZzhjA==, tableContent=null), ArticleFig(id=1240748861858304959, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=EN, label=Fig.2, caption=Gender stratification Analysis of injury Disease burden in Chinese population from 1990 to 2019, figureFileSmall=KqrlnfK7ux0s7O0732I/KA==, figureFileBig=gz8+zVWEM4Pvd8uUXrBJNw==, tableContent=null), ArticleFig(id=1240748861933802441, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=CN, label=图2, caption=1990—2019年中国人群伤害疾病负担性别分层分析

注：A为不同性别人群伤害发病率变化趋势；B为不同性别人群伤害患病率变化趋势；C为不同性别人群伤害死亡率率变化趋势；D为不同性别人群伤害DALY率变化趋势。

, figureFileSmall=KqrlnfK7ux0s7O0732I/KA==, figureFileBig=gz8+zVWEM4Pvd8uUXrBJNw==, tableContent=null), ArticleFig(id=1240748862042854354, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=EN, label=Table 1, caption=

Change trend of disease burden of injury in Chinese population from 1990 to 2019

, figureFileSmall=null, figureFileBig=null, tableContent=
伤害类型指标ASR[/10万（95% UI）]AAPC[%(95% UI)]
19902019
患病率
自我伤害和人际暴力6 379.84（5 638.31~7 249.37）6 198.39（5 460.20~7 078.13）-0.10(-0.11~-0.10)
交通伤害1 715.33（1 603.12~1 858.66）2 846.71（2 654.72~3 066.26）1.76(1.69~1.81)
意外伤害8 023.52（7 408.72~8 709.77）8 684.09（8 045.02~9 425.37）0.29(0.24~0.35)
发病率
自我伤害和人际暴力463.81(384.56~548.70)362.49(293.59~435.79)-0.86（-0.88~-0.83）
交通伤害575.12(490.69~673.01)1 029.76(880.09~1 204.74)2.03（1.96~2.09）
意外伤害4 824.88(4 182.46~5 605.97)4 746.48(4 211.64~5 385.54)-0.08（-0.33~0.20）
死亡率
自我伤害和人际暴力24.25（19.83~27.62）7.65（6.47~9.08）-3.99(-4.15~-3.83)
交通伤害21.75（18.58~30.18）15.29（12.73~17.80）-1.12(-1.21~-0.99)
意外伤害37.03（33.51~41.30）21.26（15.53~24.92）-2.01(-2.25~-1.80)
DALY率
自我伤害和人际暴力1 108.92（912.49~1 263.98）360.54（310.13~420.62）-3.82(-3.93~-3.69)
交通伤害1 232.72（1 073.60~1 638.90）859.58（739.79~975.26）-1.24(-1.34~-1.10)
意外伤害2 373.99（2 153.53~2 616.31）1 102.27（919.15~1 253.72）-2.74(-2.96~-2.55)
), ArticleFig(id=1240748862177072088, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=CN, label=表1, caption=

1990—2019年中国人群伤害的疾病负担变化趋势

, figureFileSmall=null, figureFileBig=null, tableContent=
伤害类型指标ASR[/10万（95% UI）]AAPC[%(95% UI)]
19902019
患病率
自我伤害和人际暴力6 379.84（5 638.31~7 249.37）6 198.39（5 460.20~7 078.13）-0.10(-0.11~-0.10)
交通伤害1 715.33（1 603.12~1 858.66）2 846.71（2 654.72~3 066.26）1.76(1.69~1.81)
意外伤害8 023.52（7 408.72~8 709.77）8 684.09（8 045.02~9 425.37）0.29(0.24~0.35)
发病率
自我伤害和人际暴力463.81(384.56~548.70)362.49(293.59~435.79)-0.86（-0.88~-0.83）
交通伤害575.12(490.69~673.01)1 029.76(880.09~1 204.74)2.03（1.96~2.09）
意外伤害4 824.88(4 182.46~5 605.97)4 746.48(4 211.64~5 385.54)-0.08（-0.33~0.20）
死亡率
自我伤害和人际暴力24.25（19.83~27.62）7.65（6.47~9.08）-3.99(-4.15~-3.83)
交通伤害21.75（18.58~30.18）15.29（12.73~17.80）-1.12(-1.21~-0.99)
意外伤害37.03（33.51~41.30）21.26（15.53~24.92）-2.01(-2.25~-1.80)
DALY率
自我伤害和人际暴力1 108.92（912.49~1 263.98）360.54（310.13~420.62）-3.82(-3.93~-3.69)
交通伤害1 232.72（1 073.60~1 638.90）859.58（739.79~975.26）-1.24(-1.34~-1.10)
意外伤害2 373.99（2 153.53~2 616.31）1 102.27（919.15~1 253.72）-2.74(-2.96~-2.55)
), ArticleFig(id=1240748862357427176, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=EN, label=Table 2, caption=

Injury disease burden of different genders in China from 1990 to 2019

, figureFileSmall=null, figureFileBig=null, tableContent=
伤害类型指标ASR[/10万（95% UI）]
1990
男女
患病率
自我伤害和人际暴力4 543.93（4 033.00~5 131.41）8 342.36（7 303.29~9 509.98）
交通伤害1 995.78（1 866.18~2 163.96）1 431.22（1 332.08~1 547.34）
意外伤害9 442.28（8 677.98~10287.66）6 503.90(6 024.15~7 020.66)
发病率
自我伤害和人际暴力549.36（432.32~667.03）371.35(319.64~430.20)
交通伤害672.61（567.27~790.25）470.05（399.13~548.27）
意外伤害5 924.25（5 029.19~7 054.54）3 613.97（3 216.73~4 078.65）
死亡率
自我伤害和人际暴力25.01(15.27~ 30.06)23.82(19.81~28.13)
交通伤害30.80(25.01~ 46.86)12.44(10.61~14.34)
意外伤害46.63(40.87~ 53.60)27.52(24.53~30.82)
DALY率
自我伤害和人际暴力1 104.53（722.42~1 303.05）1 117.39 （939.99~1 320.60）
交通伤害1 688.72（1 409.15~2 437.97）747.91（846.07~652.44）
意外伤害2 916.88(2 608.28~3 278.72)1 795.08(1 613.90~1 997.44)
伤害类型指标ASR[/10万（95% UI）]
2019
男女
患病率
自我伤害和人际暴力4 348.86（3 855.95~4931.54）8 162.57（7 119.93~9 328.65）
交通伤害3 383.54（3 158.67~3 651.29）2 326.60(2 168.72~2 512.04)
意外伤害10 257.63（9 463.~11 169.09）7 054.96(6 536.37~7 649.18)
发病率
自我伤害和人际暴力466.39（373.83~565.12）250.48（205.04~299.67）
交通伤害1 233.34（1 052.73~1 442.11）817.85（699.79~955.64）
意外伤害5 777.22（5 055.74~6 677.25）3 613.88（3 272.40~4 007.57）
死亡率
自我伤害和人际暴力9.97(7.81 ~12.94)5.59(4.50~6.88)
交通伤害22.93(18.06~ 27.88)7.70(6.24~9.26)
意外伤害28.52（20.60~ 34.90）14.41(10.14~17.55)
DALY率
自我伤害和人际暴力428.34（346.99~535.80）293.11（245.10~347.84）
交通伤害1 233.80(1 021.41~1 444.86)471.21(402.03~544.00)
意外伤害1 454.06(1 184.85~1 680.59)730.80(614.19~852.78)
伤害类型指标AAPC[%(95% UI)]
男女
患病率
自我伤害和人际暴力-0.15(-0.16~-0.15)-0.09(-0.10~-0.08)
交通伤害1.84(1.80~1.87)1.69(1.63~1.74)
意外伤害0.29(0.24~0.34)0.33(0.26~0.39)
发病率
自我伤害和人际暴力-0.57(-0.61~-0.55)-1.37(-1.43~-1.33)
交通伤害2.12(2.08~2.16)1.93(1.83~1.99)
意外伤害-0.84(-1.44~-0.18)-0.81(-1.48~-0.12)
死亡率
自我伤害和人际暴力-3.18(-3.31~-3.04)-4.84(-5.00~-4.66)
交通伤害-0.96(-1.06~-0.86)-1.63(-1.78~-1.46)
意外伤害-1.74(-1.99~-1.53)-2.20(-2.55~-1.85)
DALY率
自我伤害和人际暴力-3.30(-3.39~-3.19)-4.45(-4.61~-4.28)
交通伤害-1.07(-1.16~-0.95)-1.72(-1.88~-1.46)
意外伤害-2.31(-2.52~-2.12)-3.56(-3.96~-3.19)
), ArticleFig(id=1240748862483256301, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=CN, label=表2, caption=

1990—2019年中国不同性别人群的伤害疾病负担

, figureFileSmall=null, figureFileBig=null, tableContent=
伤害类型指标ASR[/10万（95% UI）]
1990
男女
患病率
自我伤害和人际暴力4 543.93（4 033.00~5 131.41）8 342.36（7 303.29~9 509.98）
交通伤害1 995.78（1 866.18~2 163.96）1 431.22（1 332.08~1 547.34）
意外伤害9 442.28（8 677.98~10287.66）6 503.90(6 024.15~7 020.66)
发病率
自我伤害和人际暴力549.36（432.32~667.03）371.35(319.64~430.20)
交通伤害672.61（567.27~790.25）470.05（399.13~548.27）
意外伤害5 924.25（5 029.19~7 054.54）3 613.97（3 216.73~4 078.65）
死亡率
自我伤害和人际暴力25.01(15.27~ 30.06)23.82(19.81~28.13)
交通伤害30.80(25.01~ 46.86)12.44(10.61~14.34)
意外伤害46.63(40.87~ 53.60)27.52(24.53~30.82)
DALY率
自我伤害和人际暴力1 104.53（722.42~1 303.05）1 117.39 （939.99~1 320.60）
交通伤害1 688.72（1 409.15~2 437.97）747.91（846.07~652.44）
意外伤害2 916.88(2 608.28~3 278.72)1 795.08(1 613.90~1 997.44)
伤害类型指标ASR[/10万（95% UI）]
2019
男女
患病率
自我伤害和人际暴力4 348.86（3 855.95~4931.54）8 162.57（7 119.93~9 328.65）
交通伤害3 383.54（3 158.67~3 651.29）2 326.60(2 168.72~2 512.04)
意外伤害10 257.63（9 463.~11 169.09）7 054.96(6 536.37~7 649.18)
发病率
自我伤害和人际暴力466.39（373.83~565.12）250.48（205.04~299.67）
交通伤害1 233.34（1 052.73~1 442.11）817.85（699.79~955.64）
意外伤害5 777.22（5 055.74~6 677.25）3 613.88（3 272.40~4 007.57）
死亡率
自我伤害和人际暴力9.97(7.81 ~12.94)5.59(4.50~6.88)
交通伤害22.93(18.06~ 27.88)7.70(6.24~9.26)
意外伤害28.52（20.60~ 34.90）14.41(10.14~17.55)
DALY率
自我伤害和人际暴力428.34（346.99~535.80）293.11（245.10~347.84）
交通伤害1 233.80(1 021.41~1 444.86)471.21(402.03~544.00)
意外伤害1 454.06(1 184.85~1 680.59)730.80(614.19~852.78)
伤害类型指标AAPC[%(95% UI)]
男女
患病率
自我伤害和人际暴力-0.15(-0.16~-0.15)-0.09(-0.10~-0.08)
交通伤害1.84(1.80~1.87)1.69(1.63~1.74)
意外伤害0.29(0.24~0.34)0.33(0.26~0.39)
发病率
自我伤害和人际暴力-0.57(-0.61~-0.55)-1.37(-1.43~-1.33)
交通伤害2.12(2.08~2.16)1.93(1.83~1.99)
意外伤害-0.84(-1.44~-0.18)-0.81(-1.48~-0.12)
死亡率
自我伤害和人际暴力-3.18(-3.31~-3.04)-4.84(-5.00~-4.66)
交通伤害-0.96(-1.06~-0.86)-1.63(-1.78~-1.46)
意外伤害-1.74(-1.99~-1.53)-2.20(-2.55~-1.85)
DALY率
自我伤害和人际暴力-3.30(-3.39~-3.19)-4.45(-4.61~-4.28)
交通伤害-1.07(-1.16~-0.95)-1.72(-1.88~-1.46)
意外伤害-2.31(-2.52~-2.12)-3.56(-3.96~-3.19)
), ArticleFig(id=1240748862575530998, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=EN, label=Table 3, caption=

Injury disease burden of different age groups in China from 1990 to 2019

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄组伤害类型发病率（/10万）患病率（/10万）
19902019AAPC(%)19902019AAPC(%)
自我伤害
0~9173.8390.23-2.27701.51646.68-0.26
10~24607.05468.01-0.926 745.946 445.35-0.18
25~49682.98509.07-1.029 800.019 527.96-0.11
50~69308.15297.72-0.126 599.736 375.74-0.14
≥70219.78207.77-0.195 873.375 481.07-0.24
交通伤害
0~9295.94415.451.17122.78145.630.59
10~24501.96855.861.83513.70697.501.06
25~49782.541 396.512.011 753.772 922.151.78
50~69663.941 357.362.493 936.356 768.621.89
≥70473.72991.612.575 350.2610 373.692.31
意外伤害
0~95 438.924 204.97-0.821 413.801 058.86-0.98
10~244 990.194 531.03-0.473 952.703 554.43-0.34
25~495 114.355 007.85-0.498 507.529 014.960.21
50~693 558.114 342.450.8214 860.0416 442.080.36
≥703 876.756 515.261.8422 933.4431 832.241.15
年龄组伤害类型死亡率（/10万）DALY率（/10万）
19902019AAPC(%)19902019AAPC(%)
自我伤害
0~93.850.56-4.72157.6125.55-6.00
10~2415.513.93-4.601 152.83341.33-4.12
25~4926.407.29-4.561 519.69481.30-3.87
50~6935.8312.04-3.871 208.36449.36-3.37
≥7080.9235.90-2.811 329.92590.32-2.80
交通伤害
0~917.614.92-4.24697.89196.44-4.27
10~2413.999.62-1.171 010.46706.77-1.18
25~4924.4518.18-1.001 399.021 104.08-0.80
50~6928.8623.61-0.581 154.761 114.71-0.13
≥7034.7536.510.26840.321 063.350.88
意外伤害
0~973.8214.76-5.252 966.60604.36-5.19
10~2416.868.70-2.421 362.59732.01-2.12
25~4916.8912.16-1.251 207.82906.59-0.88
50~6928.1820.37-1.171 449.401 189.88-0.72
≥7099.01118.200.662 290.002 620.800.51
), ArticleFig(id=1240748862692971521, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=CN, label=表3, caption=

1990—2019年中国不同年龄人群伤害疾病负担

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄组伤害类型发病率（/10万）患病率（/10万）
19902019AAPC(%)19902019AAPC(%)
自我伤害
0~9173.8390.23-2.27701.51646.68-0.26
10~24607.05468.01-0.926 745.946 445.35-0.18
25~49682.98509.07-1.029 800.019 527.96-0.11
50~69308.15297.72-0.126 599.736 375.74-0.14
≥70219.78207.77-0.195 873.375 481.07-0.24
交通伤害
0~9295.94415.451.17122.78145.630.59
10~24501.96855.861.83513.70697.501.06
25~49782.541 396.512.011 753.772 922.151.78
50~69663.941 357.362.493 936.356 768.621.89
≥70473.72991.612.575 350.2610 373.692.31
意外伤害
0~95 438.924 204.97-0.821 413.801 058.86-0.98
10~244 990.194 531.03-0.473 952.703 554.43-0.34
25~495 114.355 007.85-0.498 507.529 014.960.21
50~693 558.114 342.450.8214 860.0416 442.080.36
≥703 876.756 515.261.8422 933.4431 832.241.15
年龄组伤害类型死亡率（/10万）DALY率（/10万）
19902019AAPC(%)19902019AAPC(%)
自我伤害
0~93.850.56-4.72157.6125.55-6.00
10~2415.513.93-4.601 152.83341.33-4.12
25~4926.407.29-4.561 519.69481.30-3.87
50~6935.8312.04-3.871 208.36449.36-3.37
≥7080.9235.90-2.811 329.92590.32-2.80
交通伤害
0~917.614.92-4.24697.89196.44-4.27
10~2413.999.62-1.171 010.46706.77-1.18
25~4924.4518.18-1.001 399.021 104.08-0.80
50~6928.8623.61-0.581 154.761 114.71-0.13
≥7034.7536.510.26840.321 063.350.88
意外伤害
0~973.8214.76-5.252 966.60604.36-5.19
10~2416.868.70-2.421 362.59732.01-2.12
25~4916.8912.16-1.251 207.82906.59-0.88
50~6928.1820.37-1.171 449.401 189.88-0.72
≥7099.01118.200.662 290.002 620.800.51
), ArticleFig(id=1240748862806216717, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=EN, label=Table 4, caption=

2020—2034 Forecast of three injury DALY rates in China

, figureFileSmall=null, figureFileBig=null, tableContent=
年份DALY率（/10万）
自我伤害和人际暴力交通伤害意外伤害
2020313.567982.8431 057.300
2021299.687973.7031 028.190
2022286.414964.648999.886
2023273.728955.678972.360
2024261.605946.790945.592
2025250.018937.986919.561
2026238.944929.263894.246
2027228.361920.621869.628
2028218.247912.060845.688
2029208.581903.578822.407
2030199.342895.175799.767
2031190.513886.851777.750
2032182.057878.603756.339
2033174.011870.433735.518
2034166.304862.338715.270
), ArticleFig(id=1240748862969794579, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240375272587980822, language=CN, label=表4, caption=

2020—2034年我国三种伤害DALY率预测

, figureFileSmall=null, figureFileBig=null, tableContent=
年份DALY率（/10万）
自我伤害和人际暴力交通伤害意外伤害
2020313.567982.8431 057.300
2021299.687973.7031 028.190
2022286.414964.648999.886
2023273.728955.678972.360
2024261.605946.790945.592
2025250.018937.986919.561
2026238.944929.263894.246
2027228.361920.621869.628
2028218.247912.060845.688
2029208.581903.578822.407
2030199.342895.175799.767
2031190.513886.851777.750
2032182.057878.603756.339
2033174.011870.433735.518
2034166.304862.338715.270
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1990—2019年中国伤害疾病负担变化趋势及预测
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宋源龙 , 杨弋星 , 董顺雨 , 张态
现代预防医学 | 流行病与统计方法 2024,51(8): 1377-1383
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现代预防医学 | 流行病与统计方法 2024, 51(8): 1377-1383
1990—2019年中国伤害疾病负担变化趋势及预测
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宋源龙, 杨弋星, 董顺雨, 张态
作者信息
  • 大理大学公共卫生学院，云南 大理 671000

    • 宋源龙（1995—），男，硕士在读，研究方向：慢病流行病

通讯作者:

张态，E-mail：
Trends and predictions of the burden of three types of injury diseases, China, 1990-2019
Yuan-long SONG, Ge-xing YANG, Shun-yu DONG, Tai ZHANG
Affiliations
  • School of Public Health, Dali University, Dali, Yunnan 671000, China
出版时间: 2024-04-25 doi: 10.20043/j.cnki.MPM.202401359
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摘要
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目的

分析1990—2019年我国伤害的疾病负担变化，并预测2020—2034年的变化趋势，为制定伤害防控策略提供依据。

方法

利用2019年全球疾病负担研究数据库，分析中国伤害的年龄标准化发病率、患病率、死亡率及伤残调整寿命年率的变化趋势，计算平均年度变化百分比；采用灰色预测模型GM（1,1）预测2020—2034年的DALY变化趋势。

结果

1990—2019年，自我伤害和人际暴力的发病率、患病率、死亡率和DALY率均呈下降趋势，其中以0~9岁人群的降幅最大（AAPC=-2.27%、-0.26%、-4.72%、-6.00%）；交通伤害的发病率和患病率呈上升趋势，死亡率和DALY率总体呈下降趋势，但≥70岁人群呈上升趋势（AAPC=0.26%、0.88%）；意外伤害的发病率总体呈下降趋势（AAPC=-0.08%），但在2006—2019年却呈上升趋势（AAPC=2.69%），死亡率和DALY率总体呈下降趋势，其中≥70岁人群的发病率、患病率、死亡率和DALY率均呈上升趋势（AAPC=1.84%、1.15%、0.66%、0.51%）。灰色预测模型显示，2020—2034年三种伤害的DALY将呈下降趋势，预计到2035年，DALY率分别降至166.304/10万、862.338/10万和715.27/10万。

结论

1990—2019年我国三种伤害的死亡率和DALY率总体呈下降趋势，但交通伤害和意外伤害的发病率仍在上升，老年人的疾病负担仍在加重。

交通伤害  /  自我伤害和人际暴力  /  意外伤害  /  疾病负担  /  灰色预测
Objective

To analyze the change of disease burden of injury in China from 1990 to 2019, and to predict the change trend from 2020 to 2034, so as to provide basis for the formulation of injury prevention and control strategies.

Methods

Using the global disease burden research database in 2019, the change trends of age-standardized incidence, prevalence, mortality and disability-adjusted life expectancy rate of injuries in China were analyzed, and the average annual change percentage was calculated.The grey prediction model GM (1) was used to predict the annual DALY change trend from 2020 to 2034.

Results

From 1990 to 2019, the incidence, prevalence, mortality and Daly rate of self-injury and interpersonal violence showed a downward trend, with the largest decrease among people aged 0-9 (AAPC=-2.27%,-0.26%,-4.72%,-6.00%). The incidence and prevalence of traffic injuries showed an upward trend, while mortality and DALY rates generally showed a downward trend, but those over 70 years old showed an upward trend (AAPC=0.26%, 0.88%). The incidence of accidental injuries showed an overall downward trend (AAPC=-0.08%), but showed an upward trend in 2006—2019 (AAPC=2.69%), and the mortality and DALY rates showed an overall downward trend, among which the morbidity, prevalence, mortality and Daly rates of people ≥ 70 years old showed an upward trend (AAPC=1.84%, 1.15%, 0.66%, 0.51%). The grey prediction model showed that the DALY of the three kinds of injuries will show a downward trend from 2020 to 2034. It is estimated that by 2035, the Daly rate will decrease to 166.304 / 100 000, 862.338 / 100 000 and 715.27 / 100 000 respectively.

Conclusion

The mortality rate and DALY rate of three kinds of injuries in China show a general downward trend from 1990 to 2019, but the incidence rate of traffic injuries and accidental injuries are still rising, and the disease burden of the elderly is still increasing.

Traffic injury  /  Self-harm and interpersonal violence  /  Accidental injury  /  Disease burden  /  Grey prediction
宋源龙, 杨弋星, 董顺雨, 张态. 1990—2019年中国伤害疾病负担变化趋势及预测. 现代预防医学, 2024 , 51 (8) : 1377 -1383 . DOI: 10.20043/j.cnki.MPM.202401359
Yuan-long SONG, Ge-xing YANG, Shun-yu DONG, Tai ZHANG. Trends and predictions of the burden of three types of injury diseases, China, 1990-2019[J]. Modern Preventive Medicine, 2024 , 51 (8) : 1377 -1383 . DOI: 10.20043/j.cnki.MPM.202401359
正文
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在中国，伤害已成为继恶性肿瘤、脑血管病、呼吸系统疾病和心脏病之后的第五大死亡原因，不仅危害居民的身体健康，而且给个人、家庭和社会带来了沉重的疾病负担和经济损失[1]。本研究通过GBD 2019数据，分析了1990—2019年我国伤害疾病负担的变化，并预测了其未来15年的变化趋势，旨在为伤害防控策略的制定提供依据。
1 资料与方法
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1.1 资料来源
资料来源于全球疾病负担（Global Burden of Disease，GBD 2019），该研究由美国华盛顿大学健康指标与评估研究所（Institute for Health Metrics and Evaluation，IHME）牵头，统一采用符合世界卫生组织健康评估报告（GATHER）指南的方法对全球204个国家和地区的328种疾病和伤害的疾病负担进行评价，具体方法详见“GBD 2019 Diseases and Injuries Collaborators”[2]。
1.2 分析指标
从GBD 2019中将伤害分为自我伤害和人际暴力（Self-harm and interpersonal violence）、交通伤害（Transport injuries）以及意外伤害（Unintentional injuries）三大类，本研究按性别和年龄组对这三类伤害发病率、患病率、死亡率和伤残调整寿命年（disability-adjustedlife years，DALYs）率的年龄标准化率（age-standardized rates，ASR）进行分析，采用平均年度变化百分比(average annual percentage change, AAPC)分析各指标的时间变化趋势，AAPC是一种综合评价包含多个区间的全局平均变化趋势的方法，通过分段区间的跨度宽度对各区间的回归系数进行加权计算，更加注重时间序列的长度和每个区间的影响力。
1.3 统计分析
使用Excel 2019整理数据，采用Joinpoint 5.0.2软件分析1990—2019年间疾病负担的变化趋势，采用Matlab R2023b软件构建灰色预测模型GM（1,1）预测2020—2034年的DALY率趋势，灰色预测模型是通过少量的、不完全的信息，建立数学模型并做出预测的一种预测方法[3]，其精度检验采用后验差检验法，后验差比C<0.35为精度好，C<0.5为精度合格，C>0.65为精度不合格[4]。
2 结果
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2.1 三种伤害的疾病负担变化趋势
1990—2019年，中国自我伤害和人际暴力的发病率、患病率、死亡率和DALY率均呈下降趋势，AAPC值分别为-0.86%和-0.10% ，死亡率由24.25/10万降至7.65/10万（AAPC=-3.99%），DALY率由1 108.92/10万降至360.54/10万（AAPC=-3.82%）。
交通伤害的发病率由575.12/10万上升至1 029.76/10万（AAPC=2.03%）,患病率由1 715.33/10万上升至2 846.71/10万（AAPC=1.76%）；死亡率和DALY率总体呈下降趋势（AAPC=-1.22%、-1.24%），但分别在1996—2004（AAPC=2.07%）和1993—2004（AAPC=0.92%）年间出现了一次短暂的上升，变化趋势见图1。
意外伤害的发病率在2000—2006年由4 796.95/10万降至3 261.32/10万（AAPC=-7.00%），随后逐年上升到2019年的4 746.48/10万(AAPC=2.69%)；患病率在2001—2005年呈下降趋势（AAPC=-6.47%），随后开始上升；1990—2019年，死亡率由37.03/10万降至21.26/10万（AAPC=-2.01%），DALY率由2 373.99/10万降至1 102.27/10万（AAPC=-2.74%）。见表1。
2.2 1990—2019年中国不同性别人群伤害疾病负担
1990—2019年，我国男女性自我伤害和人际暴力的发病率、患病率、死亡率和DALY率均呈下降趋势，（AAPC=-0.57%、-0.15%、-3.18%、-3.30%和-1.37%、-0.09%、-4.84%、-4.45%）；男性的发病率和死亡率高于女性，患病率较女性低，DALY率则2000年以前低于女性，2000年以后则高于女性。
男性交通伤害的发病率和患病率均呈上升趋势（AAPC=2.12%、1.84%），死亡率和DALY率则呈下降趋势（AAPC=-0.96%、-0.17%），女性发病率和患病率均呈上升趋势（AAPC=1.93%、1.69%），死亡率和DALY率则呈下降趋势（AAPC=-1.63%、-1.72%）；男性的发病率、患病率、死亡率和DALY率均远高于女性。
男女性意外伤害的发病率、死亡率和DALY率均呈下降趋势（AAPC=-0.84%、-1.74%、-2.31%和-0.81%、-2.20%、-3.56%），患病率则呈上升趋势（AAPC=0.29%、0.33%）；男性的发病率、患病率、死亡率和DALY率均高于女性。见表2、图2。
2.3 1990—2019年中国不同年龄人群伤害疾病负担
1990—2019年，中国不同年龄人群自我伤害和人际暴力的发病率、患病率、死亡率和DALY率均呈下降趋势，其中0~9岁人群降幅均最大（AAPC=-2.27%、-0.26%、-4.72%、-6.00%）。
1990—2019年，中国不同年龄人群交通伤害的发病率和死亡率呈上升趋势，其中以≥70岁人群的增幅最大（AAPC=2.57%、2.31%），死亡率和DALY率除≥70岁人群（AAPC=0.26%、0.88%）呈上升趋势外，其他年龄段人群均呈下降趋势。
1990—2019年，中国意外伤害的发病率和患病率随年龄的增加降幅逐渐降低，50~70岁人群的发病率和患病率则呈上升趋势（AAPC=0.82%、1.84%和0.36%、1.15%），死亡率和DALY率除≥70岁人群（0.66%、0.51%）呈上升趋势外，其他年龄段人群均呈下降趋势。
2.4 2020—2040年我国伤害疾病负担预测
建立灰色预测模型GM（1,1）前需对时间序列进行级比检验，交通伤害DALY率原序列的所有级比值都位于区间（0.938~1.067）内，自我伤害和人际暴力及意外伤害的DALY率经平移转换后序列的所有级比值也都位于区间（0.938~1.067）内，适合建立灰色预测模型，此外三个模型的C值分别为0.02、0.46和0.026，模型精度合格，平均相对误差分别为5.62%、7.27%和2.70%，模型拟合良好。预测结果显示，2020—2034年伤害所致的DALY率均呈下降趋势，至2034年自我伤害和人际暴力的DALY率为166.304/10万，交通伤害的DALY率为862.338/10万,意外伤害的DALI率为715.27/10万。见表4。
3 讨论
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1990—2019年我国自我伤害和人际暴力的疾病负担总体呈下降趋势，与Naghavi M等[5]的研究结果一致，同时男性的发病率、死亡率和DALY率高于女性，患病率则略低于女性。经济水平的快速发展，医疗技术的进步、基本公共卫生服务的广泛开展等原因是自我伤害和人际暴力疾病负担降低的主要原因，同时中国传统的性别观念使得男性需要面临更多的社会压力，这可能是男性发病率、死亡率和DALY率高于女性的原因。女性性格较男性更为细腻内敛，面对压力和人际关系造成的心理问题更难恢复，因而女性的患病率略高于男性。25~49岁人群是自我伤害和人际暴力发病的主体，王震坤等[6]认为较高的生活压力、绝望度，较低的社会经济地位、生活水平和教育程度是青壮年人群发生自伤行为的主要原因；≥70岁人群是死亡率和DALY率的主体，老人多有慢性病史，且多无收入来源，特别是空巢老人，更易产生负面情绪，从而导致了更高的死亡率和DALY率。因此，加强心理健康筛查，关注自杀相关因素，做好老年人家庭陪护是非常必要的。
1990—2019年我国交通伤害的发病率和患病率整体呈上升趋势，与James等[7]的研究结果一致，死亡率和DALY率则以2004年为转折点呈先升后降的趋势。中国经济快速发展带来的货运量增加和居民汽车保有量的增多是导致这一现象的主要原因，加之近年来微移动设备的使用更加剧了这种趋势[8]；有关研究[9]-[10]表明交通伤害会随国民经济的增长呈现先升后降得趋势，2004年正是这一重要拐点，2004—2019年间交通伤害的死亡率和DALY率出现了明显的下降。在不同时期中男性交通伤害的发病率、患病率、死亡率和DALY率均高于女性，与Qi等[11]的研究结果一致，可能与男性作为劳动力的主体更多从事交通运输工作有关[12][13]。老年人则具有较高的死亡率和DALY，这与既往的研究结果一致[14]，老年人身体机能退化，反应能力较弱，在交通事故中更容易受到伤害，损伤也更难恢复，加之几年来中国老年化加剧，老年人口增多，这使得老年人成为交通伤害的高风险人群。因此，需要加强交通执法力度，严格规范交通行为，加强交通安全教育，提高人民安全意识，同时还需加强对老年代步车的管理。
2019年我国意外伤害的发病率较1990年有所降低，但是我国意外伤害的发病率在2006—2019年出现了明显的升高，死亡率和DALY率则呈下降趋势。2006—2019年发病率的上升可能是我国城市化的迅速发展导致出现了众多的安全隐患，死亡率和DALY率的降低则和另外两种伤害一样归功于医疗技术的发展和普及，以及公众意识的提高。0~9岁儿童意外伤害的降幅最大，这可能与国家政策有关，2011年国务院发布了《中国儿童发展纲要》，对儿童意外伤害的预防做出了明确规划[15]，2019年≥70岁人群是中国意外伤害发病的高峰，同时≥70人群的发病率、患病率、死亡率和DALY率均呈上升趋势，这与张春华等[16]的研究结果相似，究其原因可能是老年人口增多，且老年人身体机能衰退,协调性差,且多患有慢性非传染性疾病等有关[17]。对此，在城市建设过程中应更加注重符合老人、儿童等弱势人群的安全防护设施。
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2024年第51卷第8期
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doi: 10.20043/j.cnki.MPM.202401359
  • 接收时间：2024-01-22
  • 首发时间：2026-03-16
  • 出版时间：2024-04-25
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    大理大学公共卫生学院，云南 大理 671000

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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