Article(id=1320428878359802814, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320428830876086873, articleNumber=null, orderNo=null, doi=10.11847/zgggws1148528, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1753372800000, receivedDateStr=2025-07-25, revisedDate=1764345600000, revisedDateStr=2025-11-29, acceptedDate=1772985600000, acceptedDateStr=2026-03-09, onlineDate=1792744376983, onlineDateStr=2026-10-23, pubDate=1788969600000, pubDateStr=2026-09-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792744376983, onlineIssueDateStr=2026-10-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792744376983, creator=13701087609, updateTime=1792744376983, updator=13701087609, issue=Issue{id=1320428830876086873, tenantId=1146029695717560320, journalId=1319373219989389464, year='2026', volume='42', issue='9', pageStart='1025', pageEnd='1152', issueExtLink='null', onlineDate='null', pubDate='1788969600000', pubDateStr='2026-09-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1792744365662, creator='13701087609', updateTime=1792746244140, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320436709859381360, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320428830876086873, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320436709859381361, tenantId=1146029695717560320, journalId=1319373219989389464, issueId=1320428830876086873, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1115, endPage=1121, ext={EN=ArticleExt(id=1320428878548546495, articleId=1320428878359802814, tenantId=1146029695717560320, journalId=1319373219989389464, language=EN, title=Mortality characteristics and life loss status for four major types of chronic diseases in Qinghai province, China (2015–2022): based on the data from national-level mortality surveillance sites, columnId=1320427686514770171, journalTitle=Chinese Journal of Public Health, columnName=Survey and Report, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the mortality characteristics, life loss status, and temporal trends of four major types of chronic diseases (malignant tumors, cardiovascular and cerebrovascular diseases, chronic respiratory diseases, and diabetes mellitus) in Qinghai province from 2015 to 2022, thus providing a scientific basis for the prevention and control of these diseases in the region.

Methods

A total of 77 582 death case records were collected from 10 national-level mortality surveillance sites in the Mortality Surveillance System of Qinghai Province during 2015–2022. Indicators including crude mortality rate (CMR), standardized mortality rate (SMR), age-specific mortality rate (ASMR), avoidable potential years of life lost (PYLL), avoidable potential years of life lost rate (PYLLR), and avoidable average years of life lost (AYLL) of the four major types of chronic diseases were analyzed. The average annual percent change (AAPC) was used to describe their temporal trends.

Results

From 2015 to 2022 in Qinghai province, the CMRs, preventable crude mortality rates, and treatable crude mortality rates of the four major types of chronic diseases all showed an increasing trend (AAPC = 4.363%, 2.047%, and 3.011%, respectively; all P < 0.05), while no statistically significant differences were observed in the trends of SMR, preventable standardized mortality rate, and treatable standardized mortality rate (all P > 0.05). From 2015 to 2022, increases were observed in the CMR, preventable crude mortality rate, and treatable crude mortality rate in males, urban populations, and rural populations, the CMR in females and pastoral populations, and the treatable crude mortality rate in pastoral populations (all P < 0.05). Only the treatable standardized mortality rate of urban populations showed an upward trend (AAPC = 2.853%, P = 0.002). The mortality rates of the four major types of chronic diseases in Qinghai province increased with the increase in age (all P < 0.001), and the avoidable age-specific mortality rate in males was consistently higher than that in females (all P < 0.05). The avoidable mortality rate was the lowest in urban populations across all age groups. The results of the life loss analysis showed that the treatable PYLL and treatable PYLLR of the four major types of chronic diseases in Qinghai province from 2015 to 2022 increased, while the preventable AYLL and treatable AYLL decreased (all P < 0.05). From 2015 to 2022, the PYLL in males, as well as the PYLL, preventable PYLL, treatable PYLL, and treatable PYLLR in urban populations increased; the AYLL and preventable AYLL in males, AYLL and treatable AYLL in females, PYLL in rural populations, and AYLL, preventable AYLL, and treatable AYLL in rural and pastoral populations decreased (all P < 0.05).

Conclusions

From 2015 to 2022, the mortality rates of the four major types of chronic diseases in Qinghai province presented an upward trend, and this upward trend became more pronounced with the increase in age. The burden of life loss in urban areas was aggravated, whereas rural and pastoral areas achieved remarkable effects in reducing the average life loss of the population with chronic diseases. Reducing treatable and preventable deaths of the population shall serve as the goal for future prevention and control work

, authors=Lili XU1, Minghui ZHANG2, Ning FAN1, Qiongyue SHA1, Shuling GUO1, Suxia ZHOU1, Zhihua XU1, Peng GUO1, authorsList=Lili XU, Minghui ZHANG, Ning FAN, Qiongyue SHA, Shuling GUO, Suxia ZHOU, Zhihua XU, Peng GUO, authorCompany=null, correspAuthors=Lili XU, authorNote=null, correspAuthorsNote=
XU Lili, E-mail:
, copyrightStatement=Copyright © 2026 Chinese Journal of Public Health. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1320428881685885904, articleId=1320428878359802814, tenantId=1146029695717560320, journalId=1319373219989389464, language=CN, title=2015—2022年青海省四大类慢性病死亡特征及减寿分析:基于国家级死因监测点数据, columnId=1320427686770622717, journalTitle=中国公共卫生, columnName=调查报告与分析, runingTitle=null, highlight=null, articleAbstract=
目的

分析2015—2022年青海省恶性肿瘤、心脑血管疾病、呼吸系统疾病和糖尿病四大类慢性病的死亡特征及其寿命损失情况和变化趋势,为该地区四大类慢性病的预防控制提供参考依据。

方法

收集2015—2022年青海省死因监测系统中10个国家级死因监测点的77 582例死亡个案数据,分析四大类慢性病的粗死亡率、标化死亡率、年龄别死亡率、可避免的潜在减寿年数(PYLL)、可避免的减寿率(PYLLR)和可避免的平均寿命损失年(AYLL)等指标,并采用平均年度变化百分比(AAPC)描述其变化趋势。

结果

2015—2022年青海省四大类慢性病的粗死亡率、可预防粗死亡率和可治疗粗死亡率均呈上升趋势(AAPC=4.363%、2.047%和3.011%,均P<0.05);但标化死亡率、可预防标化死亡率和可治疗标化死亡率变化趋势差异均无统计学意义(均P>0.05)。不同特征人群中,2015—2022年四大类慢性病男性、城市和农村人群的粗死亡率、可预防粗死亡率和可治疗粗死亡率,女性和牧区人群的粗死亡率以及牧区人群的可治疗粗死亡率均呈上升趋势(均P<0.05)。城市人群可治疗标化死亡率变化呈上升趋势(AAPC=2.853%,P=0.002)。2015—2022年青海省四大类慢性病死亡率均随年龄的增长呈上升趋势(均P<0.001);男性人群可避免的年龄别死亡率始终高于女性人群(均P<0.05);各年龄段城市人群可避免死亡率均最低。死亡减寿分析结果显示,2015—2022年青海省四大类慢性病可治疗的PYLL和可治疗的PYLLR均呈上升趋势,可预防的AYLL和可治疗的AYLL均呈下降趋势(均P<0.05);不同特征人群中,2015—2022年青海省四大类慢性病男性人群PYLL以及城市人群PYLL、可预防的PYLL、可治疗的PYLL和可治疗的PYLLR均呈上升趋势;男性人群AYLL和可预防的AYLL、女性人群AYLL和可治疗的AYLL、农村人群PYLL以及农村和牧区人群AYLL、可预防的AYLL、可治疗的AYLL均呈下降趋势(均P<0.05)。

结论

2015—2022年青海省四大类慢性病死亡率呈上升趋势,随年龄增长上升趋势明显;农村和牧区在降低慢性病人群平均寿命损失上成效突出,城市的寿命损失负担加重,降低人群可治疗和可预防的死亡是今后慢性病防控的重点目标。

, authors=徐莉立1, *, *, 张明慧2, 范宁1, 沙琼玥1, 郭淑玲1, 周素霞1, 许志华1, 郭鹏1, authorsList=徐莉立, 张明慧, 范宁, 沙琼玥, 郭淑玲, 周素霞, 许志华, 郭鹏, authorCompany=null, correspAuthors=徐莉立, authorNote=

徐莉立(1974—),主任医师,硕士,研究方向:传染病和慢性病防控

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徐莉立,E-mail:
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Differences across the lifespan between females and males in the top 20 causes of disease burden globally: a systematic analysis of the Global Burden of Disease Study 2021[J]. The Lancet Public Health, 2024, 9(5): e282-e294., articleTitle=null, refAbstract=null), Reference(id=1320428895476756534, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=27, rfOrder=26, authorNames=null, journalName=null, refType=null, unstructuredReference=杨婷. 城镇化对城乡居民健康状况的影响——基于HAPC模型的分析[D]. 武汉: 华中科技大学, 2023., articleTitle=null, refAbstract=null), Reference(id=1320428895548059703, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, doi=null, pmid=null, pmcid=null, year=null, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=28, rfOrder=27, authorNames=null, journalName=null, refType=null, unstructuredReference=程明梅, 余倩. 城镇化、社会经济地位与居民健康差距[J]. 中国卫生政策研究, 2023, 16(10): 17-25., articleTitle=null, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1320428881920766929, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, xref=1, ext=[AuthorCompanyExt(id=1320428881929155538, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, companyId=1320428881920766929, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Qinghai Center for Disease Prevention and Control, Xining 810021, China), AuthorCompanyExt(id=1320428881941738451, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, companyId=1320428881920766929, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1青海省疾病预防控制中心,西宁 810021)]), AuthorCompany(id=1320428882008847316, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, xref=2, ext=[AuthorCompanyExt(id=1320428882017235925, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, companyId=1320428882008847316, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2Department of Public Health, Qinghai University School of Medicine, Xining 810007, China), AuthorCompanyExt(id=1320428882025624534, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, companyId=1320428882008847316, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2青海大学医学院公共卫生系,西宁 810007)])], figs=[ArticleFig(id=1320428890682667023, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=EN, label=Fig.1, caption=Trends in age-specific and avoidable mortality rates of four major types of chronic diseases among different populations in Qinghai province, 2015–2022, figureFileSmall=4ovQT1y+UZqoinxCwLf2Sw==, figureFileBig=eCEOeGKFL6kSJDu4wmbALQ==, tableContent=null), ArticleFig(id=1320428890758164496, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=CN, label=图1, caption=2015—2022年青海省四大类慢性病不同特征人群年龄别死亡率和可避免死亡率变化趋势, figureFileSmall=4ovQT1y+UZqoinxCwLf2Sw==, figureFileBig=eCEOeGKFL6kSJDu4wmbALQ==, tableContent=null), ArticleFig(id=1320428890967879697, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=EN, label=Tab.1, caption=

Mortality rates and temporal trends of four major types of chronic diseases in Qinghai province, 2015–2022

, figureFileSmall=null, figureFileBig=null, tableContent=
特征年份死亡情况可预防死亡情况可治疗死亡情况
粗死亡率/
(1/10万)
AAPC/%标化死亡率/
(1/10万)
AAPC/%粗死亡率/
(1/10万)
AAPC/%标化死亡率/
(1/10万)
AAPC/%粗死亡率/
(1/10万)
AAPC/%标化死亡率/
(1/10万)
AAPC/%
男性2015419.263.744 a562.430.661144.692.267 a162.95−0.39368.482.883 a75.690.934
2022584.60630.62184.64174.2986.6581.80
女性2015296.615.122 a363.301.24081.181.18682.25−1.05942.672.85343.530.616
2022458.33430.6692.6977.1255.2445.75
城市2015313.916.066 b347.781.51078.262.408 a73.34−0.11642.675.170 b35.812.853 a
2022481.23420.9191.6774.8055.2446.31
农村2015401.303.032 a549.650.865129.823.130 a147.43−0.73171.452.268 a80.58−1.373
2022537.72573.83176.35153.9186.8376.02
牧区2015360.403.566 a543.741.456135.661.139176.11−1.72057.122.586 a72.11−0.041
2022514.75640.29168.51180.6274.9879.63
合计2015357.754.363 a456.680.932112.862.047 a120.84−0.85955.543.011 a58.920.252
2022522.74526.07139.73123.8671.3163.26
), ArticleFig(id=1320428891072737298, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=CN, label=表1, caption=

2015—2022年青海省四大类慢性病死亡情况及变化趋势

, figureFileSmall=null, figureFileBig=null, tableContent=
特征年份死亡情况可预防死亡情况可治疗死亡情况
粗死亡率/
(1/10万)
AAPC/%标化死亡率/
(1/10万)
AAPC/%粗死亡率/
(1/10万)
AAPC/%标化死亡率/
(1/10万)
AAPC/%粗死亡率/
(1/10万)
AAPC/%标化死亡率/
(1/10万)
AAPC/%
男性2015419.263.744 a562.430.661144.692.267 a162.95−0.39368.482.883 a75.690.934
2022584.60630.62184.64174.2986.6581.80
女性2015296.615.122 a363.301.24081.181.18682.25−1.05942.672.85343.530.616
2022458.33430.6692.6977.1255.2445.75
城市2015313.916.066 b347.781.51078.262.408 a73.34−0.11642.675.170 b35.812.853 a
2022481.23420.9191.6774.8055.2446.31
农村2015401.303.032 a549.650.865129.823.130 a147.43−0.73171.452.268 a80.58−1.373
2022537.72573.83176.35153.9186.8376.02
牧区2015360.403.566 a543.741.456135.661.139176.11−1.72057.122.586 a72.11−0.041
2022514.75640.29168.51180.6274.9879.63
合计2015357.754.363 a456.680.932112.862.047 a120.84−0.85955.543.011 a58.920.252
2022522.74526.07139.73123.8671.3163.26
), ArticleFig(id=1320428891169206291, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=EN, label=Tab.2, caption=

Mortality rates and changing trends of the four major types of chronic diseases by age groups in Qinghai province, 2015–2022 (per 100 000 )

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄/岁2015年2016年2017年2018年2019年2020年2021年2022年AAPC/%t值P值
0~7.1510.195.0011.988.7213.986.118.301.5040.2630.801
5~2.764.573.624.511.044.024.021.80−5.538−0.6740.526
10~7.0710.077.862.941.792.767.366.00−5.518−0.3000.764
15~7.897.9014.728.488.547.4812.165.69−2.534−0.5330.613
20~9.918.6013.665.839.8215.8015.8014.908.5021.6630.147
25~23.7924.6923.2114.5616.6116.2717.138.59−11.110−3.6860.010
30~31.3029.7713.9432.3927.8326.8423.4920.22−2.851−0.6370.548
35~39.0552.9736.7738.5042.4941.9243.2538.11−0.821−0.4360.678
40~82.7595.2684.0275.0087.4488.8375.6581.09−1.153−0.9210.393
45~146.79138.43138.51143.27148.86153.51135.48149.290.4260.5940.574
50~350.64428.29446.65456.40274.88267.63220.25257.55−8.573−2.9530.026
55~418.56472.82410.88459.95533.29514.54538.02572.944.4624.5150.004
60~955.881 083.471 049.961 059.05859.57826.30701.75760.38−5.443−3.7390.010
65~1 490.171 427.501 588.941 446.681 545.661 406.841 476.781 548.510.1660.2320.824
70~2 376.072 265.192 501.722 214.682 532.322 319.812 382.392 609.160.9751.1250.303
75~4 230.404 161.484 534.444 265.785 351.394 582.524 555.235 270.362.7142.2930.062
80~8 318.918 361.989 661.849 735.999 526.0910 422.179 984.1411 279.733.9125.4930.002
≥8513 252.17 a14 871.27 a17 525.33 a17 842.74 a19 530.98 a13 786.45 a14 194.94 a16 768.59 a0.9390.4040.700
), ArticleFig(id=1320428891257286676, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=CN, label=表2, caption=

2015—2022年青海省四大类慢性病不同年龄段死亡率(1/10万)及变化趋势

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄/岁2015年2016年2017年2018年2019年2020年2021年2022年AAPC/%t值P值
0~7.1510.195.0011.988.7213.986.118.301.5040.2630.801
5~2.764.573.624.511.044.024.021.80−5.538−0.6740.526
10~7.0710.077.862.941.792.767.366.00−5.518−0.3000.764
15~7.897.9014.728.488.547.4812.165.69−2.534−0.5330.613
20~9.918.6013.665.839.8215.8015.8014.908.5021.6630.147
25~23.7924.6923.2114.5616.6116.2717.138.59−11.110−3.6860.010
30~31.3029.7713.9432.3927.8326.8423.4920.22−2.851−0.6370.548
35~39.0552.9736.7738.5042.4941.9243.2538.11−0.821−0.4360.678
40~82.7595.2684.0275.0087.4488.8375.6581.09−1.153−0.9210.393
45~146.79138.43138.51143.27148.86153.51135.48149.290.4260.5940.574
50~350.64428.29446.65456.40274.88267.63220.25257.55−8.573−2.9530.026
55~418.56472.82410.88459.95533.29514.54538.02572.944.4624.5150.004
60~955.881 083.471 049.961 059.05859.57826.30701.75760.38−5.443−3.7390.010
65~1 490.171 427.501 588.941 446.681 545.661 406.841 476.781 548.510.1660.2320.824
70~2 376.072 265.192 501.722 214.682 532.322 319.812 382.392 609.160.9751.1250.303
75~4 230.404 161.484 534.444 265.785 351.394 582.524 555.235 270.362.7142.2930.062
80~8 318.918 361.989 661.849 735.999 526.0910 422.179 984.1411 279.733.9125.4930.002
≥8513 252.17 a14 871.27 a17 525.33 a17 842.74 a19 530.98 a13 786.45 a14 194.94 a16 768.59 a0.9390.4040.700
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Life losses from deaths of four major types of chronic diseases in Qinghai province, 2015–2022

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特征年份PYLL/人年AAPC/%PYLLR/‰AAPC/%AYLL/年AAPC/%
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202233 585.80584.60630.62
女性201514 823.92−0.115296.61−0.622363.30−5.287 b
202215 321.08458.33430.66
城市201510 645.685.140 a313.91−2.371347.78−4.307
202215 406.16481.23420.91
农村201518 635.40−1.045 a401.300.255549.65−3.642 a
202217 430.84537.72573.83
牧区201513 137.04−0.098360.400.694543.74−4.030 a
202213 974.00514.75640.29
合计201542 418.121.239357.753.284456.68−3.397
202248 906.88522.74526.07
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2015—2022年青海省四大类慢性病死亡减寿情况

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特征年份PYLL/人年AAPC/%PYLLR/‰AAPC/%AYLL/年AAPC/%
男性201527 594.201.839 a419.260.865562.43−2.773 a
202233 585.80584.60630.62
女性201514 823.92−0.115296.61−0.622363.30−5.287 b
202215 321.08458.33430.66
城市201510 645.685.140 a313.91−2.371347.78−4.307
202215 406.16481.23420.91
农村201518 635.40−1.045 a401.300.255549.65−3.642 a
202217 430.84537.72573.83
牧区201513 137.04−0.098360.400.694543.74−4.030 a
202213 974.00514.75640.29
合计201542 418.121.239357.753.284456.68−3.397
202248 906.88522.74526.07
), ArticleFig(id=1320428891517333527, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=EN, label=Tab.4, caption=

Life losses from preventable deaths of four major types of chronic diseases in Qinghai province, 2015–2022

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特征年份PYLL/人年AAPC/%PYLLR/‰AAPC/%AYLL/年AAPC/%
男性201514 487.581.71917.500.78912.09−1.442 a
202217 918.9020.0210.84
女性20156 502.521.8467.831.4399.64−0.730
20227 152.828.379.03
城市20155 042.743.612 a8.411.86310.75−0.543
20226 748.809.4510.30
农村20158 706.342.25914.991.43511.55−1.644 a
202210 297.0017.9310.17
牧区20157 241.02−0.09115.120.03511.15−1.096 a
20227 990.4417.3410.29
合计201520 990.101.52412.650.85411.21−1.173 a
202225 071.7214.3310.26
), ArticleFig(id=1320428891597025304, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=CN, label=表4, caption=

2015—2022年青海省四大类慢性病可预防死亡减寿情况

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特征年份PYLL/人年AAPC/%PYLLR/‰AAPC/%AYLL/年AAPC/%
男性201514 487.581.71917.500.78912.09−1.442 a
202217 918.9020.0210.84
女性20156 502.521.8467.831.4399.64−0.730
20227 152.828.379.03
城市20155 042.743.612 a8.411.86310.75−0.543
20226 748.809.4510.30
农村20158 706.342.25914.991.43511.55−1.644 a
202210 297.0017.9310.17
牧区20157 241.02−0.09115.120.03511.15−1.096 a
20227 990.4417.3410.29
合计201520 990.101.52412.650.85411.21−1.173 a
202225 071.7214.3310.26
), ArticleFig(id=1320428891672522777, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=EN, label=Tab.5, caption=

Life losses from treatable deaths of four major types of chronic diseases in Qinghai province, 2015–2022

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特征年份PYLL/人年AAPC/%PYLLR/‰AAPC/%AYLL/年AAPC/%
男性20157 726.821.9129.330.96113.63−1.671
20229 201.9810.2811.87
女性20154 005.322.2644.821.74111.30−2.123 a
20224 550.625.339.64
城市20152 521.187.039 a4.215.215 a10.820.053
20224 361.886.1010.82
农村20155 465.90−0.1299.41−0.24913.17−2.466 a
20225 388.569.3910.81
牧区20153 740.060.0877.810.21213.67−2.312 a
20223 966.688.6111.48
合计201511 732.141.815 a7.071.136 a12.73−1.817 a
202213 752.607.8611.02
), ArticleFig(id=1320428891752214555, tenantId=1146029695717560320, journalId=1319373219989389464, articleId=1320428878359802814, language=CN, label=表5, caption=

2015—2022年青海省四大类慢性病可治疗死亡减寿情况

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男性20157 726.821.9129.330.96113.63−1.671
20229 201.9810.2811.87
女性20154 005.322.2644.821.74111.30−2.123 a
20224 550.625.339.64
城市20152 521.187.039 a4.215.215 a10.820.053
20224 361.886.1010.82
农村20155 465.90−0.1299.41−0.24913.17−2.466 a
20225 388.569.3910.81
牧区20153 740.060.0877.810.21213.67−2.312 a
20223 966.688.6111.48
合计201511 732.141.815 a7.071.136 a12.73−1.817 a
202213 752.607.8611.02
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2015—2022年青海省四大类慢性病死亡特征及减寿分析:基于国家级死因监测点数据
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徐莉立 1, *, * , 张明慧 2 , 范宁 1 , 沙琼玥 1 , 郭淑玲 1 , 周素霞 1 , 许志华 1 , 郭鹏 1
中国公共卫生 | 调查报告与分析 2026,42(9): 1115-1121
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中国公共卫生 |调查报告与分析 2026 , 42 (9) : 1115 -1121
2015—2022年青海省四大类慢性病死亡特征及减寿分析:基于国家级死因监测点数据
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徐莉立1, *, * , 张明慧2, 范宁1, 沙琼玥1, 郭淑玲1, 周素霞1, 许志华1, 郭鹏1
作者信息
  • 1青海省疾病预防控制中心,西宁 810021
  • 2青海大学医学院公共卫生系,西宁 810007
通讯作者:
徐莉立,E-mail:
作者简介:

徐莉立(1974—),主任医师,硕士,研究方向:传染病和慢性病防控

Mortality characteristics and life loss status for four major types of chronic diseases in Qinghai province, China (2015–2022): based on the data from national-level mortality surveillance sites
Lili XU1 , Minghui ZHANG2, Ning FAN1, Qiongyue SHA1, Shuling GUO1, Suxia ZHOU1, Zhihua XU1, Peng GUO1
Affiliations
  • 1Qinghai Center for Disease Prevention and Control, Xining 810021, China
  • 2Department of Public Health, Qinghai University School of Medicine, Xining 810007, China
  • Corresponding Author:
    XU Lili, E-mail:
出版时间: 2026-09-10 doi: 10.11847/zgggws1148528
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目的

分析2015—2022年青海省恶性肿瘤、心脑血管疾病、呼吸系统疾病和糖尿病四大类慢性病的死亡特征及其寿命损失情况和变化趋势,为该地区四大类慢性病的预防控制提供参考依据。

方法

收集2015—2022年青海省死因监测系统中10个国家级死因监测点的77 582例死亡个案数据,分析四大类慢性病的粗死亡率、标化死亡率、年龄别死亡率、可避免的潜在减寿年数(PYLL)、可避免的减寿率(PYLLR)和可避免的平均寿命损失年(AYLL)等指标,并采用平均年度变化百分比(AAPC)描述其变化趋势。

结果

2015—2022年青海省四大类慢性病的粗死亡率、可预防粗死亡率和可治疗粗死亡率均呈上升趋势(AAPC=4.363%、2.047%和3.011%,均P<0.05);但标化死亡率、可预防标化死亡率和可治疗标化死亡率变化趋势差异均无统计学意义(均P>0.05)。不同特征人群中,2015—2022年四大类慢性病男性、城市和农村人群的粗死亡率、可预防粗死亡率和可治疗粗死亡率,女性和牧区人群的粗死亡率以及牧区人群的可治疗粗死亡率均呈上升趋势(均P<0.05)。城市人群可治疗标化死亡率变化呈上升趋势(AAPC=2.853%,P=0.002)。2015—2022年青海省四大类慢性病死亡率均随年龄的增长呈上升趋势(均P<0.001);男性人群可避免的年龄别死亡率始终高于女性人群(均P<0.05);各年龄段城市人群可避免死亡率均最低。死亡减寿分析结果显示,2015—2022年青海省四大类慢性病可治疗的PYLL和可治疗的PYLLR均呈上升趋势,可预防的AYLL和可治疗的AYLL均呈下降趋势(均P<0.05);不同特征人群中,2015—2022年青海省四大类慢性病男性人群PYLL以及城市人群PYLL、可预防的PYLL、可治疗的PYLL和可治疗的PYLLR均呈上升趋势;男性人群AYLL和可预防的AYLL、女性人群AYLL和可治疗的AYLL、农村人群PYLL以及农村和牧区人群AYLL、可预防的AYLL、可治疗的AYLL均呈下降趋势(均P<0.05)。

结论

2015—2022年青海省四大类慢性病死亡率呈上升趋势,随年龄增长上升趋势明显;农村和牧区在降低慢性病人群平均寿命损失上成效突出,城市的寿命损失负担加重,降低人群可治疗和可预防的死亡是今后慢性病防控的重点目标。

四大类慢性病  /  恶性肿瘤  /  心脑血管疾病  /  慢性呼吸系统疾病  /  糖尿病  /  死亡特征  /  减寿分析  /  青海省
Objective

To analyze the mortality characteristics, life loss status, and temporal trends of four major types of chronic diseases (malignant tumors, cardiovascular and cerebrovascular diseases, chronic respiratory diseases, and diabetes mellitus) in Qinghai province from 2015 to 2022, thus providing a scientific basis for the prevention and control of these diseases in the region.

Methods

A total of 77 582 death case records were collected from 10 national-level mortality surveillance sites in the Mortality Surveillance System of Qinghai Province during 2015–2022. Indicators including crude mortality rate (CMR), standardized mortality rate (SMR), age-specific mortality rate (ASMR), avoidable potential years of life lost (PYLL), avoidable potential years of life lost rate (PYLLR), and avoidable average years of life lost (AYLL) of the four major types of chronic diseases were analyzed. The average annual percent change (AAPC) was used to describe their temporal trends.

Results

From 2015 to 2022 in Qinghai province, the CMRs, preventable crude mortality rates, and treatable crude mortality rates of the four major types of chronic diseases all showed an increasing trend (AAPC = 4.363%, 2.047%, and 3.011%, respectively; all P < 0.05), while no statistically significant differences were observed in the trends of SMR, preventable standardized mortality rate, and treatable standardized mortality rate (all P > 0.05). From 2015 to 2022, increases were observed in the CMR, preventable crude mortality rate, and treatable crude mortality rate in males, urban populations, and rural populations, the CMR in females and pastoral populations, and the treatable crude mortality rate in pastoral populations (all P < 0.05). Only the treatable standardized mortality rate of urban populations showed an upward trend (AAPC = 2.853%, P = 0.002). The mortality rates of the four major types of chronic diseases in Qinghai province increased with the increase in age (all P < 0.001), and the avoidable age-specific mortality rate in males was consistently higher than that in females (all P < 0.05). The avoidable mortality rate was the lowest in urban populations across all age groups. The results of the life loss analysis showed that the treatable PYLL and treatable PYLLR of the four major types of chronic diseases in Qinghai province from 2015 to 2022 increased, while the preventable AYLL and treatable AYLL decreased (all P < 0.05). From 2015 to 2022, the PYLL in males, as well as the PYLL, preventable PYLL, treatable PYLL, and treatable PYLLR in urban populations increased; the AYLL and preventable AYLL in males, AYLL and treatable AYLL in females, PYLL in rural populations, and AYLL, preventable AYLL, and treatable AYLL in rural and pastoral populations decreased (all P < 0.05).

Conclusions

From 2015 to 2022, the mortality rates of the four major types of chronic diseases in Qinghai province presented an upward trend, and this upward trend became more pronounced with the increase in age. The burden of life loss in urban areas was aggravated, whereas rural and pastoral areas achieved remarkable effects in reducing the average life loss of the population with chronic diseases. Reducing treatable and preventable deaths of the population shall serve as the goal for future prevention and control work

four major types of chronic diseases  /  malignant tumors  /  cardiovascular and cerebrovascular diseases  /  chronic respiratory diseases  /  diabetes mellitus  /  mortality characteristics  /  life loss analysis  /  Qinghai province
徐莉立, 张明慧, 范宁, 沙琼玥, 郭淑玲, 周素霞, 许志华, 郭鹏. 2015—2022年青海省四大类慢性病死亡特征及减寿分析:基于国家级死因监测点数据. 中国公共卫生, 2026 , 42 (9) : 1115 -1121 . DOI: 10.11847/zgggws1148528
Lili XU, Minghui ZHANG, Ning FAN, Qiongyue SHA, Shuling GUO, Suxia ZHOU, Zhihua XU, Peng GUO. Mortality characteristics and life loss status for four major types of chronic diseases in Qinghai province, China (2015–2022): based on the data from national-level mortality surveillance sites[J]. Chinese Journal of Public Health, 2026 , 42 (9) : 1115 -1121 . DOI: 10.11847/zgggws1148528
2023年监测数据显示,中国慢性病死亡人数占比已经超过所有疾病患者总死亡数的88%[1],其中以恶性肿瘤、心脑血管疾病、呼吸系统疾病和糖尿病为代表的四大类慢性病已成为我国居民的主要死因和最重要的疾病负担[2]。青海省地处青藏高原,2020年主要慢性病早死概率为19.74%[3],明显高于全国17%的平均水平[4]。有研究表明,可避免死亡的提出可以有效评估医疗卫生服务,指导优先干预人群和资源配置重点方向[5]。为分析2015—2022年青海省恶性肿瘤、心脑血管疾病、呼吸系统疾病和糖尿病四大类慢性病的死亡特征及其寿命损失情况和变化趋势,为该地区四大类慢性病的预防控制提供参考依据,本研究收集2015—2022年青海省死因监测系统中10个国家级死因监测点的77 582例死亡个案数据,分析四大类慢性病的粗死亡率、标化死亡率、年龄别死亡率、可避免的潜在减寿年数(potential years of life lost, PYLL)、可避免的减寿率(potential years of life lost rate, PYLLR)和可避免的平均寿命损失年(average years of life lost, AYLL)等指标,并采用平均年度变化百分比(average annual percentage change, AAPC)描述其变化趋势。
2015年1月1日—2022年12月31日青海省10个国家级监测点恶性肿瘤、心脑血管疾病、呼吸系统疾病和糖尿病四大类慢性病死亡数据来源于青海省死因监测系统。收集监测点人口死亡个案资料,包括人群基本信息和死亡信息。2015—2022年人口资料来源于青海省统计局统计的户籍人口总数、性别和年龄段构成等。调查地区分为城市、农村和牧区3类,其中城市包括西宁市城东区、城西区、城北区和城中区;农村地区包括西宁市湟中区、大通县、湟源县以及海东市六县(区);牧区包括除上述地区以外的其他区域。所有数据均采用《疾病和有关健康问题的国际统计分类:第十次修订本第一卷》(International Classification of Diseases, 10th Revision, ICD-10)[6]对根本死因进行分类。具体死因编码为:恶性肿瘤(C00~C97),心脑血管疾病(I00~I99),糖尿病(E10~E14),慢性呼吸系统疾病(J30~J98)。可避免死亡分为可预防死亡和可治疗死亡。可预防死亡指主要可以通过有效的公共卫生和初级预防干预措施(即在疾病/伤害发生之前,以减少发病率)避免的死亡原因;可治疗(或可治愈)的死亡指主要可通过及时有效的卫生保健干预措施避免的死亡原因,包括二级预防和治疗(即在疾病发作后,减少病死率)[5]。可避免死亡率作为评估卫生系统绩效指标,可评估医疗干预措施有效性和卫生服务质量[7–8]。可避免死因编码采用国际标准,即2022年1月由经济合作与发展组织/欧盟统计局发表的可预防和可治疗的死亡原因清单,年龄范围为0~74岁。具体可预防死因编码为:恶性肿瘤(C00~C14、C15、C16、C22、C33~C34、C45、C43、C67、C53);心脑血管疾病(I71、I10~I13、I20~I25、I60~I69、I70、I73.9);糖尿病(E10~E14);慢性呼吸系统疾病(J40~J44、J60~J64、J66~J70、J82、J92)。可治疗死因编码为:恶性肿瘤(C53、C18~C21、C50、C54、C55、C62、C73、C81、C91.0、C91.1);心脑血管疾病(I10~I13、I15、I20~I25、I60~I69、I70、I71、I73.9、I00~I09、I26、I80、I82.9);糖尿病(E10~E14);慢性呼吸系统疾病(J30~J39、J45~J47、J80、J81、J85、J86、J90、J93、J94)[9]。2015—2022年人口学资料来源于青海省统计局。标准人口采用2010年全国人口普查数据[10]。
2015—2022年青海省四大类慢性病死亡数据由全省国家级死因监测点录入至中国疾病预防控制中心人口死亡信息登记管理系统。所有死亡数据由省、市、县三级疾病预防控制中心专业人员开展质量核查和死因编码审核。通过漏报调查和剔除重卡提高数据完整性,以根本死因进行分类统计。
采用Excel 2016软件建立死因数据库。应用SPSS 23.0统计软件以2020年青海省期望寿命73.96岁[11]为基准,对四大类慢性病粗死亡率、标化死亡率、年龄别死亡率、可避免死亡率以及可避免的PYLL、PYLLR和AYLL等指标进行计算。可避免的死亡率=单位时间内可避免死亡数/单位时间内平均人口数;可避免的PYLL=$ \sum {a}_{i}\times {d}_{i} $,其中,$ {a}_{i}=e-(i+0.5) $,$ e $为预期寿命(岁),$ i $代表年龄组(通常计算其年龄组中值),$ {a}_{i} $代表某个特定年龄组的预期寿命与实际死亡年龄之差,$ {d}_{i} $代表该年龄组可避免死亡的人数;可避免的PYLLR=可避免的PYLL/N$ \times $1 000%;其中,N代表实际总人口数;可避免的AYLL=可避免的PYLL/各年龄组可避免死亡人数[12]。采用Joinpoint 5.0统计软件计算AAPC值拟合各个率的变化趋势;采用χ2趋势检验分析不同年龄段的趋势变化,并采用χ2检验进行率的比较。检验水准为双侧检验α=0.05。
2015—2022年青海省四大类慢性病的粗死亡率、可预防粗死亡率和可治疗粗死亡率均呈上升趋势(AAPC=4.363%、2.047%和3.011%,均P<0.05);但标化死亡率、可预防标化死亡率和可治疗标化死亡率变化趋势差异均无统计学意义(均P>0.05)。不同特征人群中,2015—2022年青海省四大类慢性病男性、城市和农村人群的粗死亡率、可预防粗死亡率和可治疗粗死亡率,女性和牧区人群的粗死亡率以及牧区人群的可治疗粗死亡率均呈上升趋势(均P<0.05);仅城市人群可治疗标化死亡率呈上升趋势(AAPC=2.853%,P=0.002)。
2015—2022年青海省四大类慢性病不同年龄组居民死亡情况分析结果显示,2015—2022年青海省四大类慢性病的死亡率均随年龄的增长呈上升趋势(均P<0.001);其中,25岁~、50岁~和60岁~年龄组死亡率均呈现下降趋势,55岁~和80岁~年龄组死亡率均呈上升趋势(均P<0.05)。分性别和地区分析结果显示,四大类慢性病死亡率和可避免死亡率均随年龄增长呈上升趋势;死亡率和可避免死亡率分别从60岁~和40岁~年龄组开始明显上升;男性死亡率和可避免死亡率始终高于女性;城市死亡率和可避免死亡率均低于农村和牧区。
分析结果显示,2015—2022年青海省四大类慢性病可治疗的PYLL和可治疗的PYLLR均呈上升趋势;可预防的AYLL和可治疗的AYLL均呈下降趋势(均P<0.05)。不同特征人群中,2015—2022年青海省四大类慢性病男性人群PYLL呈上升趋势,AYLL和可预防的AYLL均呈下降趋势,女性人群AYLL和可治疗的AYLL均呈下降趋势(均P<0.05);城市人群PYLL、可预防的PYLL、可治疗的PYLL和可治疗的PYLLR均呈上升趋势;农村人群PYLL、AYLL、可预防的AYLL和可治疗的AYLL均呈下降趋势;牧区人群AYLL、可预防的AYLL和可治疗的AYLL均呈下降趋势(均P<0.05)。
本研究结果显示,2015—2022年青海省四大类慢性病的粗死亡率、可预防粗死亡率和可治疗粗死亡率均呈上升趋势(AAPC=4.363%、2.047%和3.011%,均P<0.05)。分别从2015年的357.75/10万、112.86/10万和55.54/10万上升至2022年的522.74/10万、139.73/10万和71.31/10万;不同特征人群中,2015—2022年青海省四大类慢性病男性、城市和农村人群的粗死亡率、可预防粗死亡率和可治疗粗死亡率,女性和牧区人群的粗死亡率以及牧区人群的可治疗粗死亡率均呈上升趋势(均P<0.05)。仅城市人群可治疗标化死亡率变化呈上升趋势(AAPC=2.853%,P=0.002)。
有研究表明,2015—2019年全国四大类慢性病死亡率从532.77/10万上升至556.00/10万[13]。青海省地处我国西北部,2015—2022年四大类慢性病粗死亡率上升趋势明显,标化死亡率AAPC值为0.932%,明显低于粗死亡率AAPC值的4.363%,这可能与人口老龄化程度有关。此外,本研究分析采用的数据来源于2015—2022年青海省国家级死因监测点的监测数据,死因监测与报告质量的不断提高亦会导致死亡率的上升,但整体影响有限。青海省第七次人口普查数据显示,≥60岁人口占比为12.15%,与第六次人口普查数据相比,≥60岁人口占比上升了2.70个百分点[14],但仍然明显低于同期全国平均水平(18.70%)[15],尤其是东部地区[16]。随着老龄化程度不断加深,粗死亡率预计仍将继续呈上升趋势。
本研究结果还显示,2015—2022年青海省城市地区四大类慢性病可避免死亡率在各年龄段中均最低,提示青海省城市地区慢性病防控效果明显。2015—2019年韩国癌症相关的可避免死亡率地区差异显示,经济水平低的地区可避免死亡率较高[17],与本研究结果一致。这可能与城市人群的健康素养水平高于农村人群有关[18],还可能与城市地区健康宣教普及了低盐低脂饮食、规律运动等健康生活方式降低慢性病的发生风险,从而减少可预防疾病的死亡有关[19]。本研究中,2015—2022年青海省仅可治疗的标化死亡率呈上升趋势,可治疗死亡率的核心是“疾病发生后能否通过有效医疗措施避免死亡”,其上升趋势指向治疗环节的问题[4]。不同于我国2010年与2017年城市与农村主要慢性病可避免死亡对比分析中,城市地区可避免死亡率总体呈下降趋势的结果[10]。近年来,随着“健康中国2030”规划纲要的实施,青海省医疗服务也持续改善和提升[20]。2024年人均期望寿命提高到75.1岁[21]。而本研究中城市地区人群可治疗标化死亡率的上升可能是由于城市慢性病患者治疗依从性较差,使得可治疗的疾病未及时规范治疗[22],进而引发死亡。因此,需要做好城市地区人群慢性病全周期健康管理,加强确诊患者的分级管理,完善慢性病用药保障机制,从而提高城市地区人群治疗的依从性[23]。与城市地区相比,农村和牧区可预防和可治疗的死亡率依然较高。因此,需要合理分配农村和牧区医疗资源,优化乡村健康环境,多措并举强化农牧区人群健康保障。
死亡减寿分析结果显示,2015—2022年青海省男性人群的PYLL高于女性且呈上升趋势,与上海市徐汇区[24]研究结果一致。提示男性人群慢性病死亡年龄提前,减寿年数增加。有研究表明,吸烟、饮酒、高盐饮食和职业暴露等不良生活方式和危险因素与慢性病的发病风险息息相关[25]。男性较女性健康损失更大,尤其是过早死亡导致的健康损失[26]。因此,需要加强男性人群的健康教育和慢性病早期筛查工作。同时,本研究结果显示,城市人群四大类慢性病可治疗和可预防的PYLL均呈上升趋势,PYLL作为量化死亡所造成的寿命损失的核心指标[12],其趋势的上升反映出青海省四大类慢性病对人群寿命的损害不断加重。当前慢性病防治措施尚未有效遏制可避免疾病的发生、发展和致死风险。近年来,尽管城市医疗资源相对丰富,但城市慢性病患者数量增长较快[27],这可能与城市化进程引起的身体活动减少、生活压力增大和肥胖率提高等有关[28]。因此,需要开展适合城市人群的生活方式干预以缓解城市化相关压力,降低疾病发生风险。此外,本研究结果还显示,农村人群PYLL均高于城市地区和牧区人群,张明慧等[3]研究表明1975—2015年青海省农村地区四大类慢性病粗死亡率始终高于城市地区和牧区,提示农村一直以来都是慢性病防控的重点地区。要始终以基层为重心,加强监督评估,推进优质医疗资源下沉,开展慢性病早期筛查,并对危险因素进行精准干预,从而确保农村人群慢性病的有效防控。
综上所述,2015—2022年青海省四大类慢性病的粗死亡率、可预防粗死亡率和可治疗粗死亡率均呈上升趋势,并随年龄增长上升趋势越明显;男性和城市地区人群的死亡年龄提前,减寿年数增加。因此,及时掌握青海省慢性病死亡趋势,了解重点死亡人群和地区,可以更有效地进行筛查和干预,为制定慢性病防治措施提供科学依据。但本研究仍存在一定的局限性:一是死因监测系统数据可能存在漏报情况,根本死因判定有一定的地区差异,早期数据可能低估了真实的死亡负担;其次,本研究采用国际可避免死因分类清单进行慢性病统计分析,国内也有相关研究[5]解释了该清单。但由于不同地区公共卫生体系、医疗卫生水平和预防控制能力等均存在差异,因此,还需要结合多方面因素进一步评估人群健康水平。

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2026年第42卷第9期
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doi: 10.11847/zgggws1148528
  • 接收时间:2025-07-25
  • 首发时间:2026-10-23
  • 出版时间:2026-09-10
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  • 收稿日期:2025-07-25
  • 修回日期:2025-11-29
  • 录用日期:2026-03-09
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    1青海省疾病预防控制中心,西宁 810021
    2青海大学医学院公共卫生系,西宁 810007

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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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