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Article(id=1241035816256991937, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202407164, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720800000000, receivedDateStr=2024-07-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773815595925, onlineDateStr=2026-03-18, pubDate=1733760000000, pubDateStr=2024-12-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773815595925, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773815595925, creator=13701087609, updateTime=1773815595925, updator=13701087609, issue=Issue{id=1241035810628235909, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='23', pageStart='4225', pageEnd='4416', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773815594584, creator=13701087609, updateTime=1773815743629, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241036435843764756, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241036435843764757, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035810628235909, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4272, endPage=4278, ext={EN=ArticleExt(id=1241035816663839446, articleId=1241035816256991937, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Analysis of the disease burden attributable to high fasting blood glucose in the elderly population of China from 1992 to 2021, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the current status and trends of the disease burden attributable to high fasting blood glucose related to tuberculosis in the elderly population of China from 1992 to 2021, and to conduct forecasts to provide references for the prevention and control of tuberculosis in this population.

Methods

Data on tuberculosis mortality and Disability-Adjusted Life Years (DALY) attributable to high fasting blood glucose from 1992 to 2021 were extracted from the 2021 Global Burden of Disease Study database. The percentage change in estimated annual disease burden was calculated to analyze trends. Comparisons were made from a global perspective and across different socio-demographic index (SDI) regions, employing the decomposition method established by Gupta to quantify changes in attributable mortality and DALY. The age-period-cohort (APC) model was utilized to analyze the risk of attributable mortality, while the Bayesian age-period-cohort (BAPC) model was used to predict standardized mortality rates and standardized DALY rates.

Results

In 2021, the standardized mortality rate (2.03 per 100 000)and standardized DALY rate (46.95 per 100 000) for the elderly population in China were at a moderate level globally. The attributable mortality and DALY rates for males (2.81 per 100 000 and 70.97 per 100 000, respectively) were higher than those for females (1.04 per 100 000 and 24.21 per 100 000, respectively). From 1992 to 2021, both the standardized mortality rate and standardized DALY rate for the elderly population in China showed a declining trend, with a faster decline compared to different SDI regions. The combined contributions of population growth and aging to changes in attributable mortality and DALY were 112.50% and 109.01%, respectively, while the contributions from epidemiological changes were -170.58% and-158.48%. The APC model indicated that the risk of attributable mortality initially rose with age and then declined, as well as decreased over time and across birth cohorts. The BAPC model demonstrated superior predictive performance, forecasting a declining trend in both standardized mortality rates and standardized DALY rates from 2022 to 2030.

Conclusion

The disease burden attributable to high fasting blood glucose related to tuberculosis in the elderly population of China from 1992 to 2021 remains significant. The burden is greater in males than in females, with population growth and aging being driving factors for the increasing burden. Age, period, and cohort all influence the attributable disease burden, necessitating the implementation of comprehensive prevention and control measures tailored to the characteristics of the Chinese population.

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目的

分析1992—2021年中国老年人群归因高空腹血糖的结核病疾病负担现状、变化趋势，并开展预测，为老年人群的结核病防治提供参考。

方法

提取2021全球疾病负担研究数据库中1992—2021年中国老年人群归因于高空腹血糖的结核病死亡和DALY数据资料，通过计算年估计变化百分比分析疾病负担变化趋势，并从全球视角与不同社会人口学指数地区进行比较，采用Gupta建立的分解法量化分析归因死亡数、归因DALY数的变化。利用年龄-时期-队列模型（age-period-cohort，APC）分析归因死亡风险，利用贝叶斯年龄-时期-队列模型（bayesian age-period-cohort，BAPC）预测归因标化死亡率和归因标化DALY率。

结果

2021年，中国老年人群归因标化死亡率（2.03/10万）、标化DALY率（46.95/10万）居全球中等水平；男性的归因死亡率和归因DALY率分别为2.81/10万、70.97/10万，高于女性的1.04/10万和24.21/10万。1992—2021年，中国老年人群归因标化死亡率、归因标化DALY率均呈下降趋势，且相比不同SDI地区下降速度最快。人口增长和老龄化对归因死亡数、归因DALY数变化的合计贡献分别为112.50%、109.01%，流行病学变化的贡献分别为-170.58%、-158.48%。APC模型显示，归因死亡风险随着年龄的增长先上升后下降，随着时期的递进、出生队列的推移而下降。BAPC模型预测性能优，2022—2030年归因标化死亡率、归因标化DALY率均呈下降趋势。

结论

1992—2021年中国老年人群归因高空腹血糖的结核病疾病负担仍不容忽视，男性的归因疾病负担大于女性，人口增长和老龄化是归因疾病负担上升的驱动因素，年龄、时期和队列均对归因疾病负担存在影响，需结合中国人口特点继续开展综合防治措施。

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李雪梅，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=IyiM3DUw94PzwrFIjQ3R1A==, magXml=aNrZ7QvzHNVT+rrvEx6rjA==, pdfUrl=null, pdf=U4fbA8A21YQFgT7v1PL/DA==, pdfFileSize=5102638, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=AB4gyUgnRLerQhFwVANjfQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=vpMQfQ+8lOVTmwXRhFEdjg==, mapNumber=null, authorCompany=null, fund=null, authors=

林凯（1990—），男，本科，主管医师，研究方向：传染病预防控制

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林凯（1990—），男，本科，主管医师，研究方向：传染病预防控制

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Front Public Health, 2023, 11: 1017967., articleTitle=Effects of smoking on the severity and transmission of pulmonary tuberculosis: a hospital-based case con‐trol study, refAbstract=null), Reference(id=1241069126014259583, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, doi=null, pmid=null, pmcid=null, year=2016, volume=13, issue=9, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[19], rfOrder=24, authorNames=Horton KC, MacPherson P, Houben RMGJ, journalName=PLOS Medicine, refType=null, unstructuredReference=Horton KC, MacPherson P, Houben RMGJ, et al. Sex differences in tuberculosis burden and notifications in Low- and Middle-Income countries: a systematic review and meta-analysis[J]. PLOS Medicine,2016, 13(9): e1002119., articleTitle=Sex differences in tuberculosis burden and notifications in Low- and Middle-Income countries: a systematic review and meta-analysis, refAbstract=null), Reference(id=1241069126110728578, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, doi=null, pmid=null, pmcid=null, year=2022, volume=46, issue=5, pageStart=104, pageEnd=116, url=null, language=null, rfNumber=[20], rfOrder=25, authorNames=杨涵墨, journalName=人口研究, refType=null, unstructuredReference=杨涵墨.中国人口老龄化新趋势及老年人口新特征[J].人口研究，2022，46（5）：104-116., articleTitle=中国人口老龄化新趋势及老年人口新特征, refAbstract=null), Reference(id=1241069126211391878, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, doi=null, pmid=null, pmcid=null, year=2022, volume=46, issue=5, pageStart=104, pageEnd=116, url=null, language=null, rfNumber=[20], rfOrder=26, authorNames=Yang HM, journalName=Population Research, refType=null, unstructuredReference=Yang HM. Dynamic trend of China's population ageing and new charac‐teristics of the elderly[J]. Population Research, 2022, 46(5): 104-116.(In Chinese), articleTitle=Dynamic trend of China's population ageing and new charac‐teristics of the elderly, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1241069115595608906, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, xref=null, ext=[AuthorCompanyExt(id=1241069115608191818, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, companyId=1241069115595608906, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Infectious Disease Prevention and Control Department, Yantian District Center for Disease Control and Prevention, Shenzhen, Guangdong 518000, China), AuthorCompanyExt(id=1241069115612386123, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, companyId=1241069115595608906, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=深圳市盐田区疾病预防控制中心传染病防制科，广东 深圳 518000)])], figs=[ArticleFig(id=1241069120607801501, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=EN, label=Figure 1, caption=Age-period-cohort model for the mortality rate of TB attributable to HFPG in the elderly in China from 1992 to 2021: (A)Local offset; (B)Longitudinal age curve; (C)Period RR; (D)Cohort RR, figureFileSmall=WqL5xSF0aLB1oeH4VcZ/YA==, figureFileBig=DtDE+C6fz82VPKFpx8XvPw==, tableContent=null), ArticleFig(id=1241069120737824931, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=CN, label=图1, caption=1992—2021年中国老年人群归因于HFPG的TB死亡率的年龄-时期-队列模型

注：图A局部漂移值；图B纵向年龄曲线；图C时期率比；图D队列率比。

, figureFileSmall=WqL5xSF0aLB1oeH4VcZ/YA==, figureFileBig=DtDE+C6fz82VPKFpx8XvPw==, tableContent=null), ArticleFig(id=1241069120863654061, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=EN, label=Figure 2, caption=Predictions of the burden of TB attributable to HFPG in the elderly in China from 1992 to 2021: (A) Attributable standardized mortality rate; (B) Attributable standardized DALY rate, figureFileSmall=2VCcThFcDRpiakylsprTZQ==, figureFileBig=wyIjKf2XLGDtsXK3iDol5g==, tableContent=null), ArticleFig(id=1241069120985288888, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=CN, label=图2, caption=1992—2021年中国老年人群归因于HFPG的TB疾病负担预测

注：图A归因标化死亡率预测；图B归因标化DALY率预测。

, figureFileSmall=2VCcThFcDRpiakylsprTZQ==, figureFileBig=wyIjKf2XLGDtsXK3iDol5g==, tableContent=null), ArticleFig(id=1241069121098535107, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=EN, label=Table 1, caption=

Trends in the burden of tuberculosis attributable to HFPG among the elderly population in China, globally, and across different Socio-demographic Index (SDI) regions, from 1992 to 2021

, figureFileSmall=null, figureFileBig=null, tableContent=
地区归因标化死亡率（1/10万）归因标化DALY率（1/10万）
1992年（95%UI）2021年（95%UI）EAPC(%)(95%CI)1992年（95%UI）2021年（95%UI）EAPC(%)(95%CI)
中国14.54(9.88～20.60)2.03(1.34～3.00)-6.69(-7.13～-6.25)266.29(181.82～370.51)46.95(31.02～67.53)-5.80(-6.18～-5.43)
全球23.45(16.30～31.59)13.30(9.50～17.73)-2.16(-2.36～-1.97)426.71(298.57～575.58)247.75(177.34～327.04)-2.06(-2.26～-1.86)
高SDI2.59(1.88～13.40)0.92(0.64～1.24)-4.17(-4.39～-3.95)46.70(34.04～61.37)14.92(10.60～19.95)-4.54(-4.76～-4.32)
高-中SDI5.80(3.98～8.08)1.87(1.34～2.57)-4.20(-4.54～-3.86)110.77(76.89～153.04)39.50(27.95～53.31)-3.76(-4.07～-3.45)
中SDI31.42(21.60～42.292)12.37(8.68～16.59)-3.28(-3.51～-3.05)543.53(377.06～731.13)230.32(161.68～308.35)-3.02(-3.24～-2.80)
低-中SDI75.47(51.10～103.19)43.99(31.00～59.33)-2.19(-2.40～-1.99)1 335.78(911.95～1 823.08)776.06(547.72～1 038.83)-2.19(-2.40～-1.99)
低SDI101.27(68.81～142.14)68.70(47.83～93.87)-1.65(-1.79～-1.51)1 716.90(1 171.68～2 384.91)1 171.25(820.66～1 592.95)-1.63(-1.78～-1.48)
), ArticleFig(id=1241069121203392715, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=CN, label=表1, caption=

1992—2021年中国与全球及不同SDI地区老年人群归因于HFPG的TB疾病负担变化趋势

, figureFileSmall=null, figureFileBig=null, tableContent=
地区归因标化死亡率（1/10万）归因标化DALY率（1/10万）
1992年（95%UI）2021年（95%UI）EAPC(%)(95%CI)1992年（95%UI）2021年（95%UI）EAPC(%)(95%CI)
中国14.54(9.88～20.60)2.03(1.34～3.00)-6.69(-7.13～-6.25)266.29(181.82～370.51)46.95(31.02～67.53)-5.80(-6.18～-5.43)
全球23.45(16.30～31.59)13.30(9.50～17.73)-2.16(-2.36～-1.97)426.71(298.57～575.58)247.75(177.34～327.04)-2.06(-2.26～-1.86)
高SDI2.59(1.88～13.40)0.92(0.64～1.24)-4.17(-4.39～-3.95)46.70(34.04～61.37)14.92(10.60～19.95)-4.54(-4.76～-4.32)
高-中SDI5.80(3.98～8.08)1.87(1.34～2.57)-4.20(-4.54～-3.86)110.77(76.89～153.04)39.50(27.95～53.31)-3.76(-4.07～-3.45)
中SDI31.42(21.60～42.292)12.37(8.68～16.59)-3.28(-3.51～-3.05)543.53(377.06～731.13)230.32(161.68～308.35)-3.02(-3.24～-2.80)
低-中SDI75.47(51.10～103.19)43.99(31.00～59.33)-2.19(-2.40～-1.99)1 335.78(911.95～1 823.08)776.06(547.72～1 038.83)-2.19(-2.40～-1.99)
低SDI101.27(68.81～142.14)68.70(47.83～93.87)-1.65(-1.79～-1.51)1 716.90(1 171.68～2 384.91)1 171.25(820.66～1 592.95)-1.63(-1.78～-1.48)
), ArticleFig(id=1241069121333416146, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=EN, label=Table 2, caption=

Decomposition of driving factors for the change in TB burden attributable to HFPG among the elderly population in China, globally, and across different socio-demographic index (SDI) regions from 1992 to 2021

, figureFileSmall=null, figureFileBig=null, tableContent=
地区死亡人数
1992年（95%UI）2021年（95%UI）老龄化（%）人口增长（%）流行病学变化（%）总变化（%）
中国8 765.71(5 953.98～12 410.85)3 674.72(2 414.07～5 428.78)501.63(5.72)9 359.83(106.78)-14 952.44(-170.58)-5 090.98(-58.08)
全球77 301.87(53 755.95～104 139.71)99 715.83(71 237.76～132 923.75)2 034.55(2.63)75 430.25(97.58)-55 050.84(-71.22)22 413.96(29.00)
高SDI 2 817.95(2 040.29～3 698.52)2 105.53(1 452.51～2 828.64)189.93(6.74)1 734.17(61.54)-2 636.52(-93.56)-712.42(-25.28)
高-中SDI 4 918.05(3 380.67～6 861.11)3 343.41(2 392.77～4 593.22)123.29(2.51)3 518.74(71.55)-5 216.68(-106.07)-1 574.64(-32.02)
中SDI 22 544.97(15 525.87～30 320.78)26 268.20(18 432.12～35 191.98)1 608.64(7.14)28 648.55(127.07)-26 533.96(-117.69)3 723.23(16.51)
低-中SDI 32 394.04(21 995.45～44 126.66)46 107.65(32 554.83～62 049.28)1 131.30(3.49)36 793.58(113.58)-24 211.28(-74.74)13 713.61(42.33)
低SDI14 578.53(9 916.11～20 469.83)21 834.81(15 228.57～29 783.26)678.92(4.66)14 441.96(99.06)-7 864.60(-53.95)7 256.28(49.77)
中国17.93(12.24～24.91)9.06(5.98～13.02)0.13(0.77%)19.41(108.24%)-28.41(-158.48%)-8.87(-49.46%)
全球146.94(102.86～198.2)190.08(136.01～250.93)-0.34(-0.23%)143.28(97.51%)-99.80(-67.92%)43.14(29.36%)
高SDI5.09(3.71～6.69)3.23(2.28～4.32)0.09(1.92%)2.99(58.76%)-4.96(-97.35%)-1.87(-36.67%)
高-中SDI9.85(6.84～13.62)7.23(5.12～9.77)0.03(-0.34%)7.16(72.67%)-9.75(-98.91%)-2.62(-26.59%)
中SDI42.82(29.69～57.67)51.78(36.31～69.35)0.91(2.12%)54.71(127.76%)-46.66(-108.95%)8.96(20.92%)
低-中SDI61.65(42.12～83.84)86.77(61.18～116.03)0.65(1.05%)69.64(112.97%)-45.17(-73.27%)25.12(40.74%)
低SDI27.42(18.72～38.05)40.96(28.73～55.75)0.50(1.84%)27.10(98.84%)-14.07(-51.32%)13.54(49.36%)
), ArticleFig(id=1241069121417302234, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=CN, label=表2, caption=

1992—2021年中国与全球及不同SDI地区老年人群归因于HFPG的TB疾病负担变化驱动因素分解

, figureFileSmall=null, figureFileBig=null, tableContent=
地区死亡人数
1992年（95%UI）2021年（95%UI）老龄化（%）人口增长（%）流行病学变化（%）总变化（%）
中国8 765.71(5 953.98～12 410.85)3 674.72(2 414.07～5 428.78)501.63(5.72)9 359.83(106.78)-14 952.44(-170.58)-5 090.98(-58.08)
全球77 301.87(53 755.95～104 139.71)99 715.83(71 237.76～132 923.75)2 034.55(2.63)75 430.25(97.58)-55 050.84(-71.22)22 413.96(29.00)
高SDI 2 817.95(2 040.29～3 698.52)2 105.53(1 452.51～2 828.64)189.93(6.74)1 734.17(61.54)-2 636.52(-93.56)-712.42(-25.28)
高-中SDI 4 918.05(3 380.67～6 861.11)3 343.41(2 392.77～4 593.22)123.29(2.51)3 518.74(71.55)-5 216.68(-106.07)-1 574.64(-32.02)
中SDI 22 544.97(15 525.87～30 320.78)26 268.20(18 432.12～35 191.98)1 608.64(7.14)28 648.55(127.07)-26 533.96(-117.69)3 723.23(16.51)
低-中SDI 32 394.04(21 995.45～44 126.66)46 107.65(32 554.83～62 049.28)1 131.30(3.49)36 793.58(113.58)-24 211.28(-74.74)13 713.61(42.33)
低SDI14 578.53(9 916.11～20 469.83)21 834.81(15 228.57～29 783.26)678.92(4.66)14 441.96(99.06)-7 864.60(-53.95)7 256.28(49.77)
中国17.93(12.24～24.91)9.06(5.98～13.02)0.13(0.77%)19.41(108.24%)-28.41(-158.48%)-8.87(-49.46%)
全球146.94(102.86～198.2)190.08(136.01～250.93)-0.34(-0.23%)143.28(97.51%)-99.80(-67.92%)43.14(29.36%)
高SDI5.09(3.71～6.69)3.23(2.28～4.32)0.09(1.92%)2.99(58.76%)-4.96(-97.35%)-1.87(-36.67%)
高-中SDI9.85(6.84～13.62)7.23(5.12～9.77)0.03(-0.34%)7.16(72.67%)-9.75(-98.91%)-2.62(-26.59%)
中SDI42.82(29.69～57.67)51.78(36.31～69.35)0.91(2.12%)54.71(127.76%)-46.66(-108.95%)8.96(20.92%)
低-中SDI61.65(42.12～83.84)86.77(61.18～116.03)0.65(1.05%)69.64(112.97%)-45.17(-73.27%)25.12(40.74%)
低SDI27.42(18.72～38.05)40.96(28.73～55.75)0.50(1.84%)27.10(98.84%)-14.07(-51.32%)13.54(49.36%)
), ArticleFig(id=1241069121538937056, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=EN, label=Table 3, caption=

The Wald χ2 test of the age-period-cohort model for the mortality risk of TB attributable to HFPG among the elderly in China from 1992 to 2021

, figureFileSmall=null, figureFileBig=null, tableContent=
零假设总人群男性女性
Waldχ2值P值Waldχ2值P值Waldχ2值P值
净漂移值=01 153.36<0.001479.87<0.0011 827.56<0.001
总年龄偏差=0311.18<0.001357.94<0.00167.35<0.001
总时期偏差=0185.20<0.001211.69<0.001124.24<0.001
总队列偏差=022.350.0125.83<0.00122.900.01
全时期RR值=11 261.78<0.001643.22<0.0011 937.28<0.001
全队列RR值=16 144.31<0.0016 721.61<0.0014 786.07<0.001
净漂移值=局部漂移值20.62<0.00425.52<0.00118.180.01
), ArticleFig(id=1241069121681543398, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035816256991937, language=CN, label=表3, caption=

1992—2021年中国老年人群归因于HFPG的TB的死亡风险的年龄-时期-队列模型可估计函数Wald χ2检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
零假设总人群男性女性
Waldχ2值P值Waldχ2值P值Waldχ2值P值
净漂移值=01 153.36<0.001479.87<0.0011 827.56<0.001
总年龄偏差=0311.18<0.001357.94<0.00167.35<0.001
总时期偏差=0185.20<0.001211.69<0.001124.24<0.001
总队列偏差=022.350.0125.83<0.00122.900.01
全时期RR值=11 261.78<0.001643.22<0.0011 937.28<0.001
全队列RR值=16 144.31<0.0016 721.61<0.0014 786.07<0.001
净漂移值=局部漂移值20.62<0.00425.52<0.00118.180.01
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1992—2021年中国老年人群归因于高空腹血糖的结核病疾病负担分析
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林凯 , 刘雅文 , 张陈欢 , 黄仁湛 , 徐震东 , 古丽斯 , 李雪梅
现代预防医学 | 流行病与统计方法 2024,51(23): 4272-4278
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现代预防医学 | 流行病与统计方法 2024, 51(23): 4272-4278
1992—2021年中国老年人群归因于高空腹血糖的结核病疾病负担分析
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林凯, 刘雅文, 张陈欢, 黄仁湛, 徐震东, 古丽斯, 李雪梅
作者信息
  • 深圳市盐田区疾病预防控制中心传染病防制科，广东 深圳 518000

    • 林凯（1990—），男，本科，主管医师，研究方向：传染病预防控制

通讯作者:

李雪梅，E-mail:
Analysis of the disease burden attributable to high fasting blood glucose in the elderly population of China from 1992 to 2021
Kai LIN, Ya-wen LIU, Chen-huan ZHANG, Ren-zhan HUANG, Zhen-dong XU, Li-si GU, Xue-mei LI
Affiliations
  • Infectious Disease Prevention and Control Department, Yantian District Center for Disease Control and Prevention, Shenzhen, Guangdong 518000, China
出版时间: 2024-12-10 doi: 10.20043/j.cnki.MPM.202407164
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摘要
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目的

分析1992—2021年中国老年人群归因高空腹血糖的结核病疾病负担现状、变化趋势，并开展预测，为老年人群的结核病防治提供参考。

方法

提取2021全球疾病负担研究数据库中1992—2021年中国老年人群归因于高空腹血糖的结核病死亡和DALY数据资料，通过计算年估计变化百分比分析疾病负担变化趋势，并从全球视角与不同社会人口学指数地区进行比较，采用Gupta建立的分解法量化分析归因死亡数、归因DALY数的变化。利用年龄-时期-队列模型（age-period-cohort，APC）分析归因死亡风险，利用贝叶斯年龄-时期-队列模型（bayesian age-period-cohort，BAPC）预测归因标化死亡率和归因标化DALY率。

结果

2021年，中国老年人群归因标化死亡率（2.03/10万）、标化DALY率（46.95/10万）居全球中等水平；男性的归因死亡率和归因DALY率分别为2.81/10万、70.97/10万，高于女性的1.04/10万和24.21/10万。1992—2021年，中国老年人群归因标化死亡率、归因标化DALY率均呈下降趋势，且相比不同SDI地区下降速度最快。人口增长和老龄化对归因死亡数、归因DALY数变化的合计贡献分别为112.50%、109.01%，流行病学变化的贡献分别为-170.58%、-158.48%。APC模型显示，归因死亡风险随着年龄的增长先上升后下降，随着时期的递进、出生队列的推移而下降。BAPC模型预测性能优，2022—2030年归因标化死亡率、归因标化DALY率均呈下降趋势。

结论

1992—2021年中国老年人群归因高空腹血糖的结核病疾病负担仍不容忽视，男性的归因疾病负担大于女性，人口增长和老龄化是归因疾病负担上升的驱动因素，年龄、时期和队列均对归因疾病负担存在影响，需结合中国人口特点继续开展综合防治措施。

高空腹血糖  /  结核病  /  疾病负担  /  死亡率  /  伤残调整寿命年
Objective

To analyze the current status and trends of the disease burden attributable to high fasting blood glucose related to tuberculosis in the elderly population of China from 1992 to 2021, and to conduct forecasts to provide references for the prevention and control of tuberculosis in this population.

Methods

Data on tuberculosis mortality and Disability-Adjusted Life Years (DALY) attributable to high fasting blood glucose from 1992 to 2021 were extracted from the 2021 Global Burden of Disease Study database. The percentage change in estimated annual disease burden was calculated to analyze trends. Comparisons were made from a global perspective and across different socio-demographic index (SDI) regions, employing the decomposition method established by Gupta to quantify changes in attributable mortality and DALY. The age-period-cohort (APC) model was utilized to analyze the risk of attributable mortality, while the Bayesian age-period-cohort (BAPC) model was used to predict standardized mortality rates and standardized DALY rates.

Results

In 2021, the standardized mortality rate (2.03 per 100 000)and standardized DALY rate (46.95 per 100 000) for the elderly population in China were at a moderate level globally. The attributable mortality and DALY rates for males (2.81 per 100 000 and 70.97 per 100 000, respectively) were higher than those for females (1.04 per 100 000 and 24.21 per 100 000, respectively). From 1992 to 2021, both the standardized mortality rate and standardized DALY rate for the elderly population in China showed a declining trend, with a faster decline compared to different SDI regions. The combined contributions of population growth and aging to changes in attributable mortality and DALY were 112.50% and 109.01%, respectively, while the contributions from epidemiological changes were -170.58% and-158.48%. The APC model indicated that the risk of attributable mortality initially rose with age and then declined, as well as decreased over time and across birth cohorts. The BAPC model demonstrated superior predictive performance, forecasting a declining trend in both standardized mortality rates and standardized DALY rates from 2022 to 2030.

Conclusion

The disease burden attributable to high fasting blood glucose related to tuberculosis in the elderly population of China from 1992 to 2021 remains significant. The burden is greater in males than in females, with population growth and aging being driving factors for the increasing burden. Age, period, and cohort all influence the attributable disease burden, necessitating the implementation of comprehensive prevention and control measures tailored to the characteristics of the Chinese population.

High fasting blood glucose  /  Tuberculosis  /  Disease burden  /  Mortality rate  /  Disability-adjusted life years
林凯, 刘雅文, 张陈欢, 黄仁湛, 徐震东, 古丽斯, 李雪梅. 1992—2021年中国老年人群归因于高空腹血糖的结核病疾病负担分析. 现代预防医学, 2024 , 51 (23) : 4272 -4278 . DOI: 10.20043/j.cnki.MPM.202407164
Kai LIN, Ya-wen LIU, Chen-huan ZHANG, Ren-zhan HUANG, Zhen-dong XU, Li-si GU, Xue-mei LI. Analysis of the disease burden attributable to high fasting blood glucose in the elderly population of China from 1992 to 2021[J]. Modern Preventive Medicine, 2024 , 51 (23) : 4272 -4278 . DOI: 10.20043/j.cnki.MPM.202407164
正文
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结核病（tuberculosis, TB）是由结核分枝杆菌引起的传染病，在全球，TB仍是导致不良健康结局的主要原因之一[1]。高空腹血糖（high fasting plasma glucose, HFPG）人群感染TB风险更高，且治疗效果不佳[2]，HFPG被认为是阻碍全球范围内控制TB的主要危险因素之一[3]。2019年，中国老年人群糖尿病患者数约3 550万，居世界首位，老年人群亦是TB发病的高危人群，具有发病率高且治愈率低的特点，老年人群已成为TB防治的重点和难点[4-5]。目前，中国老年人群中归因于HFPG的TB疾病负担研究暂未见报道，随着人口老龄化的加剧，相关归因疾病负担的研究对老年人群TB防治具有重要的意义。本研究使用2021全球疾病负担研究（Global Burden of Disease study, GBD 2021）相关数据，对1992—2021年中国老年人群归因于HFPG的TB疾病负担进行现状、趋势分析及预测，为TB的防治策略提供参考。
1 材料与方法
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1.1 资料来源
数据来源于GBD 2021，选择“high fasting plasma glucose”作为危险因素，选“tuberculo‐sis”作为研究疾病，提取1992—2021年中国、全球及不同社会人口学指数（socio - demographic index, SDI）地区老年人群归因于HFPG的TB分年龄、性别的死亡、伤残调整寿命年（disability adjusted life year, DALY）的数量、率及其95%不确定性区间（uncer‐tainty intervals, UI）用以分析归因于HFPG的TB疾病负担。
1.2 相关定义
1.2.1 高空腹血糖
空腹血糖大于5.3 mmol/L[6]。
1.2.2 老年人群
65岁及以上的人群定义为老年人群[5-6]。
1.3 研究方法
1.3.1 统计描述
采用死亡数、死亡率、标化死亡率、DALY数、DALY率和标化DALY率作为评价归因于HFPG的TB疾病负担指标。
1.3.2 归因疾病负担趋势分析
计算年估计变化百分比（estimated annual percentage change, EAPC）及其95%CI。当EAPC及其95%CI下限>0时，提示呈上升趋势；反之则呈下降趋势；当95%CI包含0时表示变化无统计学意义[7]。
1.3.3 归因疾病负担变化的驱动因素分解
采用Das Gupta建立的分解方法[8-9]，对1992—2021年各年归因死亡数、归因DALY数相对于1992年的变化按人口老龄化、人口增长和流行病学变化共三个因素进行量化分解。
1.3.4 基于APC模型进行死亡风险分析
采用APC模型估计年龄、时期和出生队列对死亡风险的影响[10]。采用以5年为一组，将≥65岁人群划为7个年龄组，1992—2021年划为6个时期，时期减去年龄得到12个出生队列，设置年龄、时期、出生队列中位数所在组为参照组。
1.3.5 基于BAPC模型预测归因疾病负担
以APC模型结果为基础，构建BAPC模型，采用集成嵌套拉普拉斯近似（integrated nested laplace approximation, INLA）进行贝叶斯推断[11-12]，预测2022—2030年中国老年人群归因于HFPG的TB疾病负担。分别使用1992—2011和2012—2021年时间序列为训练集、测试集评价模型的性能，评价指标采用平均绝对百分误差（mean absolute percentage error, MAPE），当MAPE值<5%、5%～9%、10%～19%、20%～49%和≥50%分别认为模型高精度、高度准确、好、合理和不准确[13]。
1.4 统计学分析
使用R 4.2.1进行统计学分析。采用双侧检验，检验水准α=0.05。
2 结果
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2.1 归因疾病负担现状、变化趋势及变化驱动因素分解
2.1.1 归因疾病负担现状
2021年，中国老年人群归因标化死亡率、归因标化DALY率均低于全球、中SDI、低-中SDI、低SDI地区，均高于高SDI、高-中SDI地区。见表1。
2021年，中国老年人群归因死亡数为3 675.42人，占全球归因死亡数的3.69%；男性归因死亡数为2 595.03人，高于女性的1 079.69人；男性归因死亡率为2.81/10万，高于女性的1.04/10万。2021年，中国老年人群归因DALY数为9.06万人年，占全球归因DALY数的4.77%；男性归因DALY数为6.55万人年，高于女性的2.51万人年；男性归因DALY率为70.97/10万，高于女性的24.21/10万。
2.1.2 全球视角的归因疾病负担变化趋势
1992—2021年，中国、全球和不同SDI地区老年人群归因标化死亡率和归因标化DALY率均呈下降趋势。中国老年人群归因标化死亡率、归因标化DALY率下降速度最快，分别为-6.69%（95%CI:-7.13%～-6.25%）和-5.80%(95%CI:-6.18%～-5.43%)。见表1。
2.1.3 全球视角的归因疾病负担变化的驱动因素分解
1992—2021年，中国、高SDI、高-中SDI地区老年人群归因死亡数和归因DALY数呈下降趋势，全球、中SDI、低-中SDI和低SDI地区则呈上升趋势，中国的下降幅度最大，分别下降58.08%和49.46%。人口增长是全球各地区疾病负担增加的主要驱动因素，对中国的贡献为106.78%、108.24%，低于中SDI、低-中SDI地区，但高于全球、高SDI、高-中SDI和低SDI地区。流行病学变化是全球各地区疾病负担下降的驱动因素，对中国的贡献为-170.58%、-158.48%，高于全球各地区。见表2。
2.2 1992—2021年中国老年人群归因死亡风险年龄、时期、队列模型
2.2.1 模型检验
1992—2021年，中国老年人群的总人群、男性和女性归因死亡风险的年龄-时期-队列模型可估计函数Waldχ2检验的零假设均有统计学意义（P<0.05），提示总人群、男性和女性归因死亡风险的变化受到年龄、时期和队列的影响。见表3。
2.2.2 模型分析
从1992—2021年，中国老年人群的总人群、男性和女性的净漂移分别为-6.87%（95%CI:-7.26%～-6.49%）、-6.25%（95%CI:-6.80%～-5.71%）和-7.86%（95%CI:-8.21%～-7.52%），提示归因死亡风险均呈下降趋势。各年龄组局部漂移值均小于0，说明各年龄组的归因死亡风险随着时间的递进而下降；女性在各年龄组的局部漂移值的绝对值均大于男性，说明女性下降趋势均大于男性。
经调整年龄和时期效应，归因死亡率的随着年龄的增长呈先上升后下降的趋势，其中男性的归因死亡率高峰为80～84岁的20.02（95%CI:19.19～20.88）/10万，女性的高峰为70～74岁的7.63（95%CI:7.24～8.05）/10万。男性各年龄组归因死亡率高于女性。
经调整年龄和队列效应，与参照时期2002—2006年（RR=1）相比，归因风险随着时期的递进而下降，在2017—2021年下降至最低（总人群RR=0.29, 95%CI:0.27～0.32; 男性RR=0.32, 95%CI:0.29～0.36;女性RR=0.25, 95%CI:0.23～0.28）。
经调整年龄和时期效应，与参照队列1922—1926年（RR=1）相比，归因死亡风险随着出生年份的推移而下降，在1952—1956年出生队列人群下降至最低（总人群RR=0.12, 95%CI:0.11～0.13; 男性RR=0.13, 95%CI:0.12～0.15; 女性RR=0.09, 95%CI:0.08～0.10）。见图1。
2.3 基于BAPC的疾病负担预测
2.3.1 模型性能
模型拟合中国老年人群归因标化死亡率和归因标化DALY率的MAPE分别为5.32%和5.53%，提示BAPC模型预测性能优。
2.3.2 预测结果
2022—2030年，中国老年人群归因标化死亡率和归因标化DALY率均呈下降趋势，其中归因标化死亡率下降至0.87/10万（95%CI:0.01～1.78），归因标化DALY率下降至19.70/10万（95%CI:1.21～38.25）。见图2。
3 讨论
收起
本研究基于GBD 2021，率先探讨了1992—2021年中国老年人群归因于HFPG的TB疾病负担现状、变化趋势并开展预测，结果显示，中国老年人群归因于HFPG的TB疾病负担有以下特征。
归因疾病负担仍较重，需持续推进各项防治策略。全球视角下，2021年，中国老年人群的归因标化死亡率、归因标化DALY率处于中等水平，与高SDI国家相比仍有差距，提示疾病负担仍不容忽视。1992—2021年，中国老年人群归因疾病负担呈下降趋势，相比不同SDI地区，中国的下降速度最快，其中归因标化死亡率下降6.69%、归因标化DALY率下降5.80%，提示中国对老年人群采取的大规模主动筛查发现TB患者、全面推行TB督导短程化学治疗、开展糖尿病患者健康管理等策略取得了巨大的成效[14-15]，需持续推进各项策略。
男性归因疾病负担高于女性。中国老年人群中，男性归因死亡数、归因死亡率、归因DALY数、归因DALY率均高于女性，与一项全球的研究结果一致[16]。男性归因疾病负担高于女性，除中国人口性别分布男性高于女性[17]有关外，可能还与男性吸烟、饮酒等其他结核分支杆菌感染危险因素发生率高于女性[18]、女性TB治疗的依从性和效果高于男性[19]、男性糖尿病发生风险更高有关，提示需对男性开展有效的健康风险沟通及个性化健康干预措施。
流行病学变化是归因疾病负担下降的主要原因。归因疾病负担变化的驱动因素分解结果显示，人口增长、人口老龄化推动着中国老年人群归因疾病负担的上升，其中人口增长对中国归因死亡数、归因DALY数的上升分别贡献了106.78%、108.24%，高于全球的平均水平，提示人口增长给中国带来了更多的医疗资源需求，中国在公共卫生政策和医疗资源规划中应予充分考虑。但潜在的流行病学变化（归因死亡风险下降）的下降抵消了归因疾病负担上升的趋势，且与全球及不同SDI地区相比，流行病学变化对中国的归因疾病负担下降的贡献度最高，这进一步说明了中国对TB及糖尿病的系列防治政策取得的巨大成效。
年龄、时期和出生队列均对归因死亡风险均存在影响。APC模型显示，1992—2021年，中国老年人群不同性别人群归因死亡风险均随着时间的递进而下降，女性的下降趋势大于男性。年龄效应方面，归因死亡风险随着年龄的增长出现先上升后下降的趋势，男性、女性的归因死亡率高峰分别在80～84岁、70～74岁，男性的峰值明显高于女性，这与糖尿病疾病负担年龄分布情况基本一致[15]，提示随着中国人口老龄化加剧，应该加强对老年人群尤其是老年男性人群的血糖监测及TB主动筛查。时期效应方面，归因死亡风险随着时期的递进而下降，不同时期采取的防治政策均对死亡风险产生显著影响，1991年的《一九九一至二〇〇〇年全国结核病防治规划》，2001年的《全国结核病防治规划（2001—2010年）》，2011年的《“健康中国2030”规划纲要》等系列适合中国国情的防治工作策略，得以让中国建立了完善的TB防治体系，归因疾病负担得到显著下降。出生队列方面，队列越年轻归因死亡风险则更低。
BAPC模型预测显示归因疾病负担呈下降趋势，但仍不容忽视。虽然BAPC模型预测显示2022—2030年归因疾病负担呈下降趋势，但归因疾病负担变化的驱动因素分解结果显示人口老龄化是疾病负担上升的驱动因素之一。目前，中国人口老龄化速度进一步加快[20]，需采取措施来预防老龄化导致的归因疾病负担升高的问题，如将老年人群的糖尿病和TB防治与深化医改、国家基本公共卫生服务工作紧密结合，不断加强对老年人群的血糖监测及TB主动筛查，加强医疗资源的配置、社会支持和关怀，确保老年患者能得到有效治疗和管理；对老年人群开展针对性健康教育，增加老年人对HFPG和TB的认识；加强相关科研工作，深入研究HFPG与TB的发病机制，助力解决阻碍结核病防治的技术难题等。
本研究仍存在一定局限性，一是GBD 2021数据是基于数学模型和统计学模型估计获得，不可避免地存在测量误差；二是暂未开展TB不同耐药情况的归因疾病负担研究，今后应予于完善。
综上所述，1992—2021年，中国老年人群归因于HFPG的TB疾病负担仍不容忽视，男性的归因疾病负担高于女性，人口增长和老龄化是归因疾病负担上升的驱动因素，年龄越大、出生队列越早归因死亡风险更高，随着人口老龄化加剧，应制定针对性的防治措施，降低归因疾病负担。
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2024年第51卷第23期
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doi: 10.20043/j.cnki.MPM.202407164
  • 接收时间：2024-07-13
  • 首发时间：2026-03-18
  • 出版时间：2024-12-10
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    深圳市盐田区疾病预防控制中心传染病防制科，广东 深圳 518000

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2种不同金属材料的力学参数
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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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