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Article(id=1324070910801621358, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202507187, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1752336000000, receivedDateStr=2025-07-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793612705183, onlineDateStr=2026-11-02, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793612705183, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793612705183, creator=13701087609, updateTime=1793612705183, updator=13701087609, issue=Issue{id=1324070892967428793, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='24', pageStart='4417', pageEnd='4608', issueExtLink='null', onlineDate='null', pubDate='1766592000000', pubDateStr='2025-12-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793612700931, creator='13701087609', updateTime=1793612772549, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324071193430602023, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324071193430602024, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324070892967428793, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=4443, endPage=4449, ext={EN=ArticleExt(id=1324070911061668207, articleId=1324070910801621358, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study and trend forecast on the burden of pancreatic cancer attributed to hyperglycemia, China, 1990-2021, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the trend of pancreatic cancer disease burden attributable to hyperglycemia in China from 1990 to 2021 and project it to 2030, and to compare the differences in disease burden characteristics and trends between China and the world and different SDI regions, in order to provide a basis for optimizing pancreatic cancer prevention and control strategies.

Methods

Based on the Global Burden of Disease Database 2021, the disease burden of pancreatic cancer attributable to hyperglycemia in China was described by the number of deaths, mortality rate, DALY, and DALY rate from 1990 to 2021, the PAF was used to rank the risk factors, and the AAPC was calculated using the Joinpoint model to analyze the difference in disease burden trends in China, globally, and in different SDI regions, and the ARIMA model was used to project to 2022-2030.

Results

The number of pancreatic cancer deaths attributable to hyperglycemia, mortality rate, DALY and DALY rate in China showed an increasing trend from 1990 to 2021. Men had higher mortality, standardized mortality, DALY rate and standardized DALY rate than women. The peaks of PAF for mortality and DALY rate were in the 75-79 and 70-74 age groups, respectively. The standardized mortality rate and standardized DALY rate were positively correlated with the SDI, and China was lower than the global average. The ARIMA model predicted that the standardized mortality rate and the standardized DALY rate would decrease to 1.13/100 000 and 25.33/100 000 in 2030, respectively.

Conclusion

The burden of pancreatic cancer disease attributable to hyperglycemia in China from 1990 to 2021 showed significant gender differences and age distribution patterns, and the burden of disease in China, although consistently lower than the global average, showed a trend of synchronous growth with that of the world and all SDI regions. Therefore, China should improve its hyperglycemia screening and management system and adopt targeted interventions for men and young and middle-aged groups to reduce the disease burden of pancreatic cancer due to hyperglycemia.

, authors=Guan-lian HE, Xue-ting WANG, Wei-guang YAO, authorsList=Guan-lian HE, Xue-ting WANG, Wei-guang YAO, authorCompany=null, correspAuthors=Wei-guang YAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1324070913737634169, articleId=1324070910801621358, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=1990—2021年基于全球视角的中国归因于高血糖的胰腺癌疾病负担分析及预测研究, columnId=1228016567632462653, journalTitle=现代预防医学, columnName=流行病与统计方法, runingTitle=null, highlight=null, articleAbstract=
目的

分析1990—2021年中国归因于高血糖的胰腺癌（PC）疾病负担趋势，并预测至2030年，同时对比中国与全球及不同社会人口学指数（SDI）地区的疾病负担特征和变化趋势差异，为优化胰腺癌防控策略提供依据。

方法

基于2021年全球疾病负担数据库，通过死亡数、死亡率、伤残调整生命年（DALY）和DALY率等描述1990—2021年中国归因于高血糖的胰腺癌疾病负担情况，采用人群归因分值（PAF）排序危险因素，使用Joinpoint模型计算年平均变化百分率（AAPC）以分析中国、全球及不同SDI地区疾病负担的趋势差异，运用ARIMA模型预测到2022—2030年。

结果

1990—2021年中国归因于高血糖的胰腺癌死亡人数、死亡率、DALY和DALY率均呈上升趋势。男性死亡率、标化死亡率、DALY率和标化DALY率均高于女性。死亡率的PAF及DALY率的峰值分别在75~79岁组和70~74岁组。标化死亡率、标化DALY率与SDI呈正相关，中国低于全球平均水平。ARIMA模型预测，2030年标化死亡率、标化DALY率将分别下降至1.13/10万和25.33/10万。

结论

1990—2021中国归因于高血糖的胰腺癌疾病负担存在显著性别差异和年龄分布规律，且始终低于全球均值，但与全球及各SDI地区均呈现同步增长趋势。因此，我国应完善高血糖筛查和管理体系，并对男性和中青年群体采取针对性干预措施，以减轻因高血糖导致的胰腺癌疾病负担。

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何冠琏（1993—），女，硕士在读，研究方向：社会医学与卫生事业管理

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姚卫光，E-mail：
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(In Chinese), articleTitle=Advances in surgical treatment following translational therapy for pancreatic cancer, refAbstract=null), Reference(id=1324070924089176522, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, doi=null, pmid=null, pmcid=null, year=2025, volume=56, issue=4, pageStart=997, pageEnd=1002, url=null, language=null, rfNumber=［20］, rfOrder=36, authorNames=李静文, 吴仲, 彭兵, journalName=四川大学学报（医学版）, refType=null, unstructuredReference=李静文，吴仲，彭兵. 困难胰腺微创手术的临床实践与质量控制策略 [J]. 四川大学学报（医学版）, 2025, 56 (4): 997-1002., articleTitle=困难胰腺微创手术的临床实践与质量控制策略, refAbstract=null), Reference(id=1324070924168868300, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, doi=null, pmid=null, pmcid=null, year=2025, volume=56, issue=4, pageStart=997, pageEnd=1002, url=null, language=null, rfNumber=［20］, rfOrder=37, authorNames=Li JW, Wu Z, Peng B, journalName=Journal of Sichuan University（Medical Edition）, refType=null, unstructuredReference=Li JW, Wu Z, Peng B. Clinical practice and quality control strategies for challenging minimally invasive pancreatic surgery [J]. Journal of Sichuan University（Medical Edition）, 2025, 56 (4): 997-1002. (In Chinese), articleTitle=Clinical practice and quality control strategies for challenging minimally invasive pancreatic surgery, refAbstract=null)], funds=[Fund(id=1324070918909211042, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, awardId=2024-2026年, language=CN, fundingSource=广州公共卫生服务体系建设研究基地资助项目(2024-2026年), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324070914018652538, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, xref=null, ext=[AuthorCompanyExt(id=1324070914031235451, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, companyId=1324070914018652538, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Health Management, Southern Medical University, Guangzhou, Guangdong 510515, China), AuthorCompanyExt(id=1324070914039624060, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, companyId=1324070914018652538, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=南方医科大学卫生管理学院，广东　广州　510515)])], figs=[ArticleFig(id=1324070917739000214, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=EN, label=Fig.1, caption=Mortality of PC attributable to hyperglycemia in China, 1990—2021, figureFileSmall=tDtDhD/rkq0XgXcRQqBslg==, figureFileBig=AeiUztn8aMOE8MkM/BRMvg==, tableContent=null), ArticleFig(id=1324070917814497687, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=CN, label=图1, caption=中国归因于高血糖的胰腺癌死亡率, figureFileSmall=tDtDhD/rkq0XgXcRQqBslg==, figureFileBig=AeiUztn8aMOE8MkM/BRMvg==, tableContent=null), ArticleFig(id=1324070918036795800, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=EN, label=Fig.2, caption=DALY rate of PC attributable to hyperglycemia in China, 1990—2021, figureFileSmall=cVI/Pc8MZCrd3C5ioKBmQQ==, figureFileBig=6VvpE5CFSPnrUGplbcSxtw==, tableContent=null), ArticleFig(id=1324070918112293273, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=CN, label=图2, caption=中国归因于高血糖的胰腺癌DALY率, figureFileSmall=cVI/Pc8MZCrd3C5ioKBmQQ==, figureFileBig=6VvpE5CFSPnrUGplbcSxtw==, tableContent=null), ArticleFig(id=1324070918187790746, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=EN, label=Fig.3, caption=Projected trends in standardized mortality and standardized DALY rates for PC attributable to hyperglycemia in China, 2022-2030, figureFileSmall=4jFuq8cYDxOQJ0oMKAy9iA==, figureFileBig=N7W4L54kqpf7sxGgZzfe8w==, tableContent=null), ArticleFig(id=1324070918267482523, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=CN, label=图3, caption=2022—2030年中国归因于高血糖的胰腺癌标化死亡率及标化DALY率变化趋势预测

注：A为标化死亡率变化趋势预测图，B为标化DALY率变化趋势预测图。

, figureFileSmall=4jFuq8cYDxOQJ0oMKAy9iA==, figureFileBig=N7W4L54kqpf7sxGgZzfe8w==, tableContent=null), ArticleFig(id=1324070918347174300, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=EN, label=Table 1, caption=

PC deaths attributed to hyperglycemia in different age groups in China, 1990—2021

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄（岁）PAF（%）死亡人数（万）死亡率（1/10万）P值
1990年2021年1990年2021年1990年2021年AAPC(95% CI)
40~448.9713.05148.79302.420.220.331.39（0.90~1.88）<0.001
45~4911.4915.27233.45647.320.450.590.74（-0.09~1.58）0.080
50~5414.0217.54507.041 467.961.061.210.53（0.20~0.85）0.001
55~5916.5719.32868.772 376.712.002.160.37（-0.12~0.87）0.145
60~6418.8121.481 078.812 857.753.053.910.99（-0.02~2.01）0.056
65~6920.6223.051 201.974 585.904.415.981.22（0.36~2.09）0.005
70~7421.9024.251 208.164 969.106.429.321.37（1.06~1.69）<0.001
75~7922.4724.67892.533 862.487.8411.661.38（0.95~1.82）<0.001
80~8422.5124.46487.112 706.949.2013.681.44（0.98~1.90）<0.001
85~9021.8623.60194.011 669.8311.5017.531.45（0.85~2.06）<0.001
90~9420.7922.0138.89489.0512.6716.681.07（0.57~1.57）<0.001
>9519.2320.163.8685.879.5413.441.17（0.69~1.64）<0.001
全人群17.9921.936 991.0326 256.340.591.853.87（3.48~4.27）<0.001
), ArticleFig(id=1324070918418477469, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=CN, label=表1, caption=

我国不同年龄组归因于高血糖的胰腺癌死亡情况

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄（岁）PAF（%）死亡人数（万）死亡率（1/10万）P值
1990年2021年1990年2021年1990年2021年AAPC(95% CI)
40~448.9713.05148.79302.420.220.331.39（0.90~1.88）<0.001
45~4911.4915.27233.45647.320.450.590.74（-0.09~1.58）0.080
50~5414.0217.54507.041 467.961.061.210.53（0.20~0.85）0.001
55~5916.5719.32868.772 376.712.002.160.37（-0.12~0.87）0.145
60~6418.8121.481 078.812 857.753.053.910.99（-0.02~2.01）0.056
65~6920.6223.051 201.974 585.904.415.981.22（0.36~2.09）0.005
70~7421.9024.251 208.164 969.106.429.321.37（1.06~1.69）<0.001
75~7922.4724.67892.533 862.487.8411.661.38（0.95~1.82）<0.001
80~8422.5124.46487.112 706.949.2013.681.44（0.98~1.90）<0.001
85~9021.8623.60194.011 669.8311.5017.531.45（0.85~2.06）<0.001
90~9420.7922.0138.89489.0512.6716.681.07（0.57~1.57）<0.001
>9519.2320.163.8685.879.5413.441.17（0.69~1.64）<0.001
全人群17.9921.936 991.0326 256.340.591.853.87（3.48~4.27）<0.001
), ArticleFig(id=1324070918510752158, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=EN, label=Table 2, caption=

DALY of PC attributable to hyperglycemia in different age groups in China, 1990—2021

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄（岁）DALY（人年）DALY率（1/10万）P值
1990年2021年1990年2021年AAPC(95% CI)
40~447 161.9414 536.3310.6715.881.38（0.91~1.85）<0.001
45~4910 080.4727 878.2919.5325.270.75（0.05~1.46）0.036
50~5419 440.5256 301.1240.7546.580.52（0.20~0.84）0.002
55~5929 315.8080 277.0267.6073.020.37（-0.12~0.86）0.140
60~6431 381.0282 879.2488.80113.530.98（-0.05~2.01）0.061
65~6929 421.65112 109.63107.84146.161.24（0.45~2.04）0.002
70~7424 358.43100 198.95129.44188.001.37（1.06~1.69）<0.001
75~7914 441.1462 310.33126.89188.141.37（0.94~1.80）<0.001
80~846 177.9234 091.01116.63172.251.43（0.83~2.03）<0.001
85~901 962.4216 771.05116.34176.061.43（0.84~2.03）<0.001
90~94341.224 288.68111.21146.271.07（0.57~1.57）<0.001
>9532.38710.3979.96111.151.12（0.65~1.60）<0.001
全人群181 127.87605 286.0815.4042.543.47（3.06~3.88）<0.001
), ArticleFig(id=1324070918594638239, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=CN, label=表2, caption=

我国不同年龄组归因于高血糖的胰腺癌DALY情况

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄（岁）DALY（人年）DALY率（1/10万）P值
1990年2021年1990年2021年AAPC(95% CI)
40~447 161.9414 536.3310.6715.881.38（0.91~1.85）<0.001
45~4910 080.4727 878.2919.5325.270.75（0.05~1.46）0.036
50~5419 440.5256 301.1240.7546.580.52（0.20~0.84）0.002
55~5929 315.8080 277.0267.6073.020.37（-0.12~0.86）0.140
60~6431 381.0282 879.2488.80113.530.98（-0.05~2.01）0.061
65~6929 421.65112 109.63107.84146.161.24（0.45~2.04）0.002
70~7424 358.43100 198.95129.44188.001.37（1.06~1.69）<0.001
75~7914 441.1462 310.33126.89188.141.37（0.94~1.80）<0.001
80~846 177.9234 091.01116.63172.251.43（0.83~2.03）<0.001
85~901 962.4216 771.05116.34176.061.43（0.84~2.03）<0.001
90~94341.224 288.68111.21146.271.07（0.57~1.57）<0.001
>9532.38710.3979.96111.151.12（0.65~1.60）<0.001
全人群181 127.87605 286.0815.4042.543.47（3.06~3.88）<0.001
), ArticleFig(id=1324070918707884448, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=EN, label=Table 3, caption=

PC burden of disease attributable to hyperglycemia in China versus global and five SDI categories, 1990-2021

, figureFileSmall=null, figureFileBig=null, tableContent=
地区标化死亡率（1/10万）P值标化DALY率（1/10万）P值
1990年2021年AAPC(95% CI)1990年2021年AAPC(95% CI)
中国0.911.251.18（0.73~1.62）<0.00120.9827.881.05（0.65~1.44）<0.001
全球1.081.571.22（1.13~1.31）<0.00122.6431.701.10（0.98~1.23）<0.001
低SDI0.230.401.76（1.66~1.86）<0.0015.198.601.65（1.57~1.73）<0.001
中低SDI0.270.632.77（2.63~2.90）<0.0016.0113.912.75（2.57~2.93）<0.001
中SDI0.691.001.34（1.11~1.56）<0.00115.1721.881.26（1.05~1.47）<0.001
中高SDI1.231.811.30（1.11~1.49）<0.00127.4038.861.15（1.02~1.28）<0.001
高SDI1.732.661.40（1.31~1.49）<0.00136.4553.801.25（1.16~1.35）<0.001
), ArticleFig(id=1324070918774993313, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324070910801621358, language=CN, label=表3, caption=

中国与全球及五类SDI地区归因于高血糖的胰腺癌疾病负担情况

, figureFileSmall=null, figureFileBig=null, tableContent=
地区标化死亡率（1/10万）P值标化DALY率（1/10万）P值
1990年2021年AAPC(95% CI)1990年2021年AAPC(95% CI)
中国0.911.251.18（0.73~1.62）<0.00120.9827.881.05（0.65~1.44）<0.001
全球1.081.571.22（1.13~1.31）<0.00122.6431.701.10（0.98~1.23）<0.001
低SDI0.230.401.76（1.66~1.86）<0.0015.198.601.65（1.57~1.73）<0.001
中低SDI0.270.632.77（2.63~2.90）<0.0016.0113.912.75（2.57~2.93）<0.001
中SDI0.691.001.34（1.11~1.56）<0.00115.1721.881.26（1.05~1.47）<0.001
中高SDI1.231.811.30（1.11~1.49）<0.00127.4038.861.15（1.02~1.28）<0.001
高SDI1.732.661.40（1.31~1.49）<0.00136.4553.801.25（1.16~1.35）<0.001
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1990—2021年基于全球视角的中国归因于高血糖的胰腺癌疾病负担分析及预测研究
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何冠琏 , 王雪婷 , 姚卫光
现代预防医学 | 流行病与统计方法 2025,52(24): 4443-4449
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现代预防医学 |流行病与统计方法 2025 , 52 (24) : 4443 -4449
1990—2021年基于全球视角的中国归因于高血糖的胰腺癌疾病负担分析及预测研究
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何冠琏, 王雪婷, 姚卫光
作者信息
  • 南方医科大学卫生管理学院，广东　广州　510515
通讯作者:
姚卫光，E-mail：
作者简介:

何冠琏（1993—），女，硕士在读，研究方向：社会医学与卫生事业管理

Study and trend forecast on the burden of pancreatic cancer attributed to hyperglycemia, China, 1990-2021
Guan-lian HE, Xue-ting WANG, Wei-guang YAO
Affiliations
  • School of Health Management, Southern Medical University, Guangzhou, Guangdong 510515, China
出版时间: 2025-12-25 doi: 10.20043/j.cnki.MPM.202507187
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摘要
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目的

分析1990—2021年中国归因于高血糖的胰腺癌（PC）疾病负担趋势，并预测至2030年，同时对比中国与全球及不同社会人口学指数（SDI）地区的疾病负担特征和变化趋势差异，为优化胰腺癌防控策略提供依据。

方法

基于2021年全球疾病负担数据库，通过死亡数、死亡率、伤残调整生命年（DALY）和DALY率等描述1990—2021年中国归因于高血糖的胰腺癌疾病负担情况，采用人群归因分值（PAF）排序危险因素，使用Joinpoint模型计算年平均变化百分率（AAPC）以分析中国、全球及不同SDI地区疾病负担的趋势差异，运用ARIMA模型预测到2022—2030年。

结果

1990—2021年中国归因于高血糖的胰腺癌死亡人数、死亡率、DALY和DALY率均呈上升趋势。男性死亡率、标化死亡率、DALY率和标化DALY率均高于女性。死亡率的PAF及DALY率的峰值分别在75~79岁组和70~74岁组。标化死亡率、标化DALY率与SDI呈正相关，中国低于全球平均水平。ARIMA模型预测，2030年标化死亡率、标化DALY率将分别下降至1.13/10万和25.33/10万。

结论

1990—2021中国归因于高血糖的胰腺癌疾病负担存在显著性别差异和年龄分布规律，且始终低于全球均值，但与全球及各SDI地区均呈现同步增长趋势。因此，我国应完善高血糖筛查和管理体系，并对男性和中青年群体采取针对性干预措施，以减轻因高血糖导致的胰腺癌疾病负担。

高血糖  /  胰腺癌  /  疾病负担  /  Jointpoint模型  /  ARIMA模型
Objective

To analyze the trend of pancreatic cancer disease burden attributable to hyperglycemia in China from 1990 to 2021 and project it to 2030, and to compare the differences in disease burden characteristics and trends between China and the world and different SDI regions, in order to provide a basis for optimizing pancreatic cancer prevention and control strategies.

Methods

Based on the Global Burden of Disease Database 2021, the disease burden of pancreatic cancer attributable to hyperglycemia in China was described by the number of deaths, mortality rate, DALY, and DALY rate from 1990 to 2021, the PAF was used to rank the risk factors, and the AAPC was calculated using the Joinpoint model to analyze the difference in disease burden trends in China, globally, and in different SDI regions, and the ARIMA model was used to project to 2022-2030.

Results

The number of pancreatic cancer deaths attributable to hyperglycemia, mortality rate, DALY and DALY rate in China showed an increasing trend from 1990 to 2021. Men had higher mortality, standardized mortality, DALY rate and standardized DALY rate than women. The peaks of PAF for mortality and DALY rate were in the 75-79 and 70-74 age groups, respectively. The standardized mortality rate and standardized DALY rate were positively correlated with the SDI, and China was lower than the global average. The ARIMA model predicted that the standardized mortality rate and the standardized DALY rate would decrease to 1.13/100 000 and 25.33/100 000 in 2030, respectively.

Conclusion

The burden of pancreatic cancer disease attributable to hyperglycemia in China from 1990 to 2021 showed significant gender differences and age distribution patterns, and the burden of disease in China, although consistently lower than the global average, showed a trend of synchronous growth with that of the world and all SDI regions. Therefore, China should improve its hyperglycemia screening and management system and adopt targeted interventions for men and young and middle-aged groups to reduce the disease burden of pancreatic cancer due to hyperglycemia.

Hyperglycemia  /  Pancreatic cancer (PC)  /  Burden of disease  /  Jointpoint model  /  ARIMA model
何冠琏, 王雪婷, 姚卫光. 1990—2021年基于全球视角的中国归因于高血糖的胰腺癌疾病负担分析及预测研究. 现代预防医学, 2025 , 52 (24) : 4443 -4449 . DOI: 10.20043/j.cnki.MPM.202507187
Guan-lian HE, Xue-ting WANG, Wei-guang YAO. Study and trend forecast on the burden of pancreatic cancer attributed to hyperglycemia, China, 1990-2021[J]. Modern Preventive Medicine, 2025 , 52 (24) : 4443 -4449 . DOI: 10.20043/j.cnki.MPM.202507187
正文
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胰腺癌（Pancreatic Cancer，PC）是一种诊断难、发展快、预后差的消化系统肿瘤[1]。据2022年全球癌症统计报告的流行病学数据显示，胰腺癌发病率位列恶性肿瘤第15位，死亡率高居第9位；其中中国新发病例11.87万，位居恶性肿瘤第10位，死亡病例10.63万，位居全部恶性肿瘤死亡的第6位[2]。根据既往数据及研究显示，1990—2019年高血糖是胰腺癌伤残调整生命年（Disability-adjust Life Years，DALY）率顺位第二危险因素，至2021年其DALY率达42.54/10万，成为首要危险因素，且85%患者在胰腺癌确诊前2~3年内，已出现高血糖、甚至糖尿病症状[3]。
已有学者对中国胰腺癌疾病负担、危险因素及未来变化趋势进行研究[4]，及证实高空腹血糖与胰腺癌风险存在正相关关系，自1990年以来中国归因于高空腹血糖的胰腺癌粗死亡率增加近2倍，标化DALY率的年度平均百分比变化（Estimated Annual Percent Changes，EAPC）高达2.04%[5]。但现有研究对单一高危因素所致胰腺癌的疾病负担分析仍显不足，也缺乏针对不同社会人口指数（Social Demographic Index，SDI）地区的差异化研究。随着生活方式、医疗保健、经济发展等显著进步，准确量化疾病负担是实施有效预防措施和早期干预的基础。因此，本研究基于GBD 2021，分析1990—2021年中国归因于高血糖的胰腺癌疾病负担及其时间变化趋势，并预测至2030年的疾病负担水平，对比中国与全球及不同SDI地区的疾病负担特征和变化趋势差异，为完善胰腺癌防控策略提供科学依据。
1　材料与方法
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1.1　数据来源
本研究数据来源于GBD 2021公开数据库，提取分析1990—2021年中国、全球及不同SDI地区归因于高血糖的胰腺癌的死亡数、死亡率、DALY和DALY率等指标，各标化率均采用GBD 2021全球标准人口年龄构成进行计算。疾病分类采用《国际疾病分类》第十版编码系统，胰腺癌对应编码为C25.0～C25.9。
1.2　评价指标
本研究采用死亡数、死亡率、人群归因分值（Population Attributable Fraction，PAF）、DALY、DALY率，及通过世界标准人口进行年龄标化后得到的年龄标化率，分析1990—2021年中国归因于高血糖的胰腺癌疾病负担，DALY的计算公式为：DALY=YLLs+YLDs，其中，YLLs代表因早死而损失的生命年，YLDs代表因疾病或伤残而损失的健康年。采用PAF衡量在特定人群中，如果消除高血糖这一危险因素，该人群胰腺癌的疾病负担能够减少的比例。PAF的计算公式为：
其中RR（x）表示危险因素（此处为高血糖）暴露水平所对应的相对危险度函数，P1（x）表示当前人群中该危险因素的实际暴露分布密度，P2（x）表示该危险因素的理论最小暴露水平所对应的密度函数。GBD基于大量已发表的文献综述和Meta分析结果，估定了高血糖导致胰腺癌的RR值。在此基础上，将计算得到的PAF分别乘以胰腺癌的总死亡数和伤残调整寿命年（DALY），最终得出可归因于高血糖的胰腺癌死亡人数及DALY。由于胰腺癌主要发病于40岁及以上年龄，因此本研究选取40岁及以上人群数据，以5岁为一个年龄组，对1990—2021年中国由高血糖所致的不同性别和不同年龄段人群的胰腺癌PAF值、死亡及DALY情况进行描述。采用标化死亡率和标化DALY率对比中国与全球及不同SDI地区归因于高血糖的胰腺癌疾病负担差异。
1.3　统计学处理
本研究采用EXCEL 2019软件进行数据整理分析。通过死亡数、死亡率、DALY和DALY率等指标描述1990—2021年中国不同性别、年龄组人群归因于高血糖的胰腺癌疾病负担特征。采用Joinpoint Regression Program 5.3.0.0软件分析疾病负担的时间变化趋势。以年份为自变量，DALY率和死亡率为因变量，计算各年龄段及不同地区归因于高血糖的胰腺癌疾病负担的年平均变化百分率（Average Annual Percentage Change，AAPC），并据此评估其长期变化趋势。连接点数量、位置及其统计学显著性通过蒙特卡洛置换检验法确定，检验水准设为α=0.05。采用R软件（Version 4.4.3）构建时间序列预测模型，筛选最优ARIMA模型预测2022—2030年中国胰腺癌归因于高血糖的疾病负担。
2　结果
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2.1　1990—2021年中国归因于高血糖的胰腺癌死亡情况
研究期间，全人群归因于高血糖的胰腺癌死亡负担显著加重，PAF从17.99%升至21.93%；归因死亡人数从6 991例激增至26 256例，增长275.8%；归因死亡率逐年上升，从0.59/10万增长到1.85/10万，增长率为213.56%，AAPC为3.87%（95% CI=3.48%~4.27%），2021年有所下降。
归因于高血糖的胰腺癌负担具有明显年龄梯度特征：从40~44岁组到75~79岁组，PAF和死亡率均随年龄增长而显著上升，其中75~79岁组的PAF达到峰值（24.67%）；85~90岁组死亡率最高，达17.53/10万。此外，1990—2021年，除45~49岁、55~59岁和60~64岁组外，各年龄组均呈现显著增长趋势（P<0.05），尤以40~44岁组（AAPC=1.39%，95% CI=0.90~1.88）和70岁以上老年组（AAPC=1.38%~1.45%）增长最大（P<0.001）。见表1。
从性别差异看，男性的死亡率始终高于女性，且差异随时间推移逐年增大；总人群的死亡率曲线介于男性和女性之间，整体保持与性别分组一致的上升态势。见图1。
2.2　1990—2021年中国归因于高血糖的胰腺癌DALY情况
研究期间，中国归因于高血糖的胰腺癌DALY负担显著上升，但从2020年起轻微回落。2021年中国因高血糖导致的胰腺癌DALY为60.53万人年，比1990年增加42.42万人年，增幅达234.2%；DALY率从15.40/10万上升至42.54/10万，增长约2.76倍，AAPC为3.47%（95% CI=3.06%~3.88%）。
从年龄差异看，我国因高血糖导致的胰腺癌DALY负担呈现显著年龄梯度特征。2021年65~69岁组DALY负担最重，达11.21万人年；从DALY率来看，70~74岁组最高（188.00/10万）。在时间趋势上，1990—2021年间各年龄组因高血糖导致的胰腺癌DALY人年数均显著增加，其中>95岁组DALY人年数增幅最大，增长率为2 093.92%，65~69岁组绝对增量最多，增加8.27万人年；除55~59岁和60~64岁组外，其他年龄组归因于高血糖的胰腺癌DALY率均显著上升，其中80~84岁组（AAPC=1.43%，95% CI=0.83%~2.03%）和85~90岁组（AAPC=1.43%，95% CI=0.84%~2.03%）增长最快，其次为40~44岁组，AAPC为1.38%（95% CI=0.91%~1.85%）。见表2。
从性别差异看，1990—2021年中国男性与女性归因于高血糖的胰腺癌DALY率均呈逐年上升趋势。男性归因于高血糖的胰腺癌DALY率始终高于女性和全人群水平，且差异随时间趋势扩大；女性始终低于全人群水平。见图2。
2.3　1990—2021年中国与全球及不同SDI地区归因于高血糖的胰腺癌疾病负担及变化趋势
2021年全球及不同SDI地区归因于高血糖的胰腺癌疾病负担呈明显梯度差异。从标化死亡率来看，高SDI地区最高（2.66/10万），中国（1.25/10万）略低于全球平均水平（1.57/10万），低SDI地区最低（0.40/10万）。归因于高血糖胰腺癌的标化DALY率也呈现相同状况，高SDI地区最高（53.80/10万），中国（27.88/10万）仍低于全球均值（31.70/10万），低SDI地区最低（8.60/10万）。
从变化趋势看，1990—2021年所有地区的标化死亡率均显著上升，中低SDI地区增速最快（AAPC=2.77%），中国AAPC为1.18%（95% CI=0.73~1.62）低于全球（AAPC=1.22%,95% CI=1.13~1.31）；标化DALY率同样普遍增长（AAPC=1.05%~2.75%），中低SDI地区增幅最大，AAPC=2.75%（95% CI=2.57~2.93），中国AAPC为1.05%（95% CI=0.65~1.44）仍慢于全球（AAPC=1.10%，95% CI=0.98~1.23）；同时，虽然低SDI地区绝对负担较低，但其标化DALY率AAPC为1.65%（95% CI=1.57~1.73）显著高于中国和全球水平。
2.4　2022—2030年归因于高血糖的胰腺癌疾病负担预测
本研究基于1990—2021年中国归因于高血糖的胰腺癌疾病负担数据，构建时间序列预测模型预测2022—2030年标化死亡率和标化DALY率。ADF检验显示原始序列非平稳，经差分处理后平稳。ARIMA模型筛选结果显示，最优标化死亡率预测模型为ARIMA（1，1，0）（AIC=-149.54，BIC=-146.67）；最优标化DALY率预测模型为ARIMA（2，1，0）（AIC=29.72，BIC=34.02）。残差诊断表明，两个模型的Ljung-Box检验结果（标化死亡率：χ2=4.75，P=0.91；标化DALY率：χ2=3.46，P=0.97）均显示残差为白噪声序列，证实模型满足独立性假设，预测效能良好。
预测结果显示，标化死亡率将平稳下降，从2022年的1.21/10万（95% CI=1.17~1.25）缓慢降至2030年的1.13/10万（95% CI=0.84~1.43）；标化DALY率预测显示先降后稳，从2022年的26.39/10万（95% CI=25.69~27.10）降至2025年的24.66/10万（95% CI=21.20~28.12）后趋于稳定，2030年预测值为25.33/10万（95% CI=19.53~31.12）。见图3。
3　讨论
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胰腺癌作为全球致死率最高的恶性肿瘤之一，其疾病负担的持续攀升已成为重大公共卫生问题[4]。本研究基于GBD 2021数据，系统分析1990—2021年间中国与全球及不同SDI地区归因于高血糖的胰腺癌疾病负担的变化特征，并预测2022—2030年期间中国的发展态势。结果显示，1990—2021年中国归因于高血糖的胰腺癌疾病负担存在性别差异和年龄分布特征，死亡人数、DALY、死亡率和DALY率均呈上升趋势，各年龄组的人群归因分值均有所上升。因此，归因于高血糖的胰腺癌仍给中国带来沉重的疾病负担，亟需采取系列干预措施。
本研究发现，1990—2021中国归因于高血糖的胰腺癌疾病负担存在明显性别差异。男性患者的死亡率、标化死亡率、DALY率和标化DALY率均高于女性，且差异逐年增大。这可能与多种因素相关：一是我国男性健康体检依从性[6]、糖尿病社区管理率和治疗率均低于女性[7]；二是女性体雌激素和内类固醇激素水平均高于男性，可降低高血糖发生率[8]，并对胰腺癌的发生发展可能具有潜在保护性作用[9]。因此，应引导男性提高体检服务利用率，注重疾病的早期诊断及干预；强化对男性行为风险的干预，注重个体化和精准化，提高其配合社区管理和治疗的主动性和积极性，改善血糖控制效果。
研究结果显示，中国归因于高血糖的胰腺癌疾病负担呈现年龄分布规律。死亡率峰值出现在85~90岁组，DALY率最高值则见于70~74岁组，这可能与人口老龄化相关[10]。值得关注的是，2019—2021年，40~44岁组人群归因于高血糖的胰腺癌的死亡率和DALY率均呈显著增长趋势，提示该人群的疾病负担持续增加。影响因素可能与生理、心理、社会等相关，生理上，年龄≧35岁是糖尿病的高危因素[11]，40岁以上人群胰腺癌发病率显著上升[12]，且长期的高血糖状态可促进肿瘤细胞增殖，并可以多种途径增强其恶化潜能[13]；心理上，中青年人群普遍存在健康风险认知偏差，认为自己比其他人更不易出现严重健康问题[14]；社会上，该群体承担主要家庭和社会责任，工作压力大、社交活动多，同时伴随不良生活方式（如作息紊乱、缺乏运动及“三高”饮食），这些因素共同增加高血糖和胰腺癌的发病风险[12,15]。因此，应加强糖尿病筛查和规范化管理，重点提升中青年糖尿病早期患者的健康风险认知水平和血糖监测依从性；基于中青年人群特征，推广物联网和可穿戴设备应用以提高自我管理效能；有针对性地向中青年人群开展健康宣教，包括膳食指导、运动建议和戒烟限酒等。
1990—2021年中国与全球五类SDI地区的归因于高血糖的胰腺癌标化死亡率和标化DALY率均显著提升，SDI与归因于高血糖的胰腺癌的标化死亡率、标化DALY率呈正相关。高SDI地区可能因高热量饮食、肥胖等代谢性危险因素聚集及人口老龄化，导致标化死亡率和标化DALY率随SDI升高而增加；低SDI地区则可能因医疗资源不足及早期筛查诊断能力欠缺，造成疾病负担评估存在偏差[16-20]。虽低SDI地区绝对负担较低，但其标化DALY率显著高于中国和全球水平；中低SDI地区也呈现最快的标化死亡率和标化DALY增长速度，说明发展中国家的高血糖及胰腺癌相关防治水平需予以关注和重视。同时，中国的标化死亡率和标化DALY率低于全球平均水平，说明中国在糖尿病规范化防治方面的成功实践，能为其他国家提供可借鉴路径。我国于2009年将2型糖尿病患者管理服务纳入国家基本公共卫生服务。近十余年来，出台系列政策、举措，推广全民健康、“三减三健”，明确糖尿病规范化管理和血糖控制率要求；通过推行医联体建设、分级诊疗、国家标准化代谢性疾病管理中心（National Metabolic Management Center，MMC）项目等，构建综合防治体系；防治指南从最早期以翻译和参考国外为主，现已根据国人循证，形成覆盖糖尿病的早期筛查、个体化治疗及并发症管理等全流程管理规范[11]。建议其他国家制定基于循证医学诊疗规范，采取系统、精准、动态的综合防治，并深化多边科研合作，依托“一带一路”、南南合作等机制平台渠道获取国际技术支持。
时间序列预测结果显示，2022—2030年中国归因于高血糖的胰腺癌疾病负担的标化死亡率平稳下降，标化DALY率在2025—2026年趋于稳定，但2027年略有上升，提示我国虽在血糖管理和胰腺癌防治方面取得一定进展和成效，但仍需持续关注和重视，要进一步加强高危人群血糖管理，提升胰腺癌早期诊断技术可及性，落实应对老龄化地区疾病负担反弹风险的相关干预措施。
GBD数据库基于系统动力学模型与统计学模型对疾病负担及其趋势进行整合分析，属于估计数据而非实际观测值，因此可能存在估计偏差。此外，ARIMA模型的预测效度有赖于历史数据的平稳性和完整性，诊疗技术突破、短期公共卫生事件或公共卫生政策调整等因素都可能会对长期预测带来不确定性，预测结果可能产生偏差，将考虑在后续研究结合未来最新数据更新模型预测结果。
基金
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  • 广州公共卫生服务体系建设研究基地资助项目(2024-2026年)
文献
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参考文献 引证文献
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2025年第52卷第24期
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doi: 10.20043/j.cnki.MPM.202507187
  • 接收时间：2025-07-13
  • 首发时间：2026-11-02
  • 出版时间：2025-12-25
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  • 收稿日期：2025-07-13
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广州公共卫生服务体系建设研究基地资助项目(2024-2026年)
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    南方医科大学卫生管理学院，广东　广州　510515

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姚卫光，E-mail：
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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