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Article(id=1311350191328953288, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349984730116963, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202601180, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1768147200000, receivedDateStr=2026-01-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579849321, onlineDateStr=2026-09-28, pubDate=1784908800000, pubDateStr=2026-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579849321, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579849321, creator=13701087609, updateTime=1790579849321, updator=13701087609, issue=Issue{id=1311349984730116963, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='14', pageStart='2497', pageEnd='2688', issueExtLink='null', onlineDate='null', pubDate='1784908800000', pubDateStr='2026-07-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790579800064, creator='13701087609', updateTime=1790588348354, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311385838924169506, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349984730116963, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311385838924169507, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349984730116963, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2656, endPage=2661, ext={EN=ArticleExt(id=1311350193463854025, articleId=1311350191328953288, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Disease burden of leukemia attributable to smoking, China, 1990-2023, columnId=1228016573156360233, journalTitle=Modern Preventive Medicine, columnName=Disease Control and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the temporal trends and driving factors of the burden of leukemia attributable to smoking in China from 1990 to 2023, and to provide evidence for prevention and control strategies.

Methods

Based on the Global Burden of Disease Study 2023 database, data on leukemia deaths and disability-adjusted life years (DALYs) attributable to smoking in China were extracted. The Joinpoint regression model was used to analyze the temporal trends of standardized rates. Decomposition analysis was employed to explore the impacts of population growth, aging, and epidemiological changes on the disease burden.

Results

From 1990 to 2023, the number of leukemia deaths attributable to smoking in China increased from 4 200 to 8 200 (an increase of 96.82%), and DALYs increased from 118 300 to 203 600 person-years (an increase of 72.13%). The age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR) showed downward trends (with average annual percent changes of -0.97% and -1.13%, respectively, P<0.001). Decomposition analysis indicated that population growth and aging were the main driving forces for the increase in the absolute value of the disease burden.

Conclusion

Although the age-standardized burden of leukemia attributable to smoking in China showed a declining trend from 1990 to 2023, the absolute burden continued to increase under the influence of factors such as population aging, and significant sex disparities were observed. Males and older adults should be prioritized in prevention and control efforts, and tobacco control interventions should be further strengthened to curb the growing burden.

, authors=Wen-zheng YANG, Zhi ZENG, Kai-ming YU, Shu-wen XIAO, Tian-hao YANG, Qian-wen SUN, authorsList=Wen-zheng YANG, Zhi ZENG, Kai-ming YU, Shu-wen XIAO, Tian-hao YANG, Qian-wen SUN, authorCompany=null, correspAuthors=Zhi ZENG, 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=1311350197729461203, articleId=1311350191328953288, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=1990—2023年中国归因于吸烟的白血病疾病负担分析, columnId=1228016573844226129, journalTitle=现代预防医学, columnName=疾病预防控制, runingTitle=null, highlight=null, articleAbstract=
目的

分析1990—2023年中国归因于吸烟的白血病负担趋势及驱动因素，为防控策略提供依据。

方法

基于2023年全球疾病负担数据库，提取中国归因于吸烟的白血病死亡和伤残调整寿命年（DALY）数据。采用Joinpoint回归模型分析标化率的时间变化趋势，利用分解分析法探究人口增长、老龄化及流行病学变化对疾病负担的影响。

结果

1990—2023年，中国归因于吸烟的白血病死亡人数从0.42万例增至0.82万例（增长96.82%），DALY从11.83万人年增至20.36万人年（增长72.13%）。标化死亡率（age-standardized mortality rate,ASMR）和标化DALY率（age-standardized DALY rate,ASDR）呈下降趋势（AAPC分别为-0.97%和-1.13%，P<0.001）。分解分析显示，人口增长和老龄化是导致疾病负担绝对值增加的主要驱动力。

结论

1990—2023年中国归因于吸烟的白血病标化疾病负担虽呈下降趋势，但受人口老龄化等因素影响，绝对负担仍持续加重且存在显著的性别差异。男性和老年人群是防控重点，需进一步强化控烟干预以遏制负担增长。

, authors=杨文正, 曾智, 于凯明, 肖舒雯, 杨添皓, 孙倩文, authorsList=杨文正, 曾智, 于凯明, 肖舒雯, 杨添皓, 孙倩文, authorCompany=null, correspAuthors=曾智, authorNote=

杨文正（2003—），男，硕士在读，研究方向：卫生政策与管理

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曾智，E-mail：
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Annual changes in the burden of leukemia attributable to smoking in China from 1990 to 2023

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指标分类具体指标时间变化值（95%CI）（%）P值
标化死亡率（ASMR）男性APC1990—2007年-1.03（-2.12～-0.79）0.042
2007—2023年-0.71（-0.91～0.29）0.088
AAPC1990—2023年-0.87（-0.98～-0.76）<0.001
女性APC1990—2002年-1.15（-1.35～-0.90）<0.001
2002—2014年-4.06（-4.35～-3.84）<0.001
2014—2023年-1.77（-2.07～-1.38）<0.001
AAPC1990—2023年-2.38（-2.45～-2.32）<0.001
总体APC1990—2018年-0.92（-1.99～0.27）0.069
2018—2021年0.24（-1.87～1.12）0.933
2021—2023年-3.46（-5.33～-0.62）0.003
AAPC1990—2023年-0.97（-1.08～-0.81）<0.001
标化DALY率（ASDR）男性APC1990—2015年-1.10（-1.32～-0.37）0.036
2015—2021年-0.12（-1.95～1.43）0.965
2021—2023年-3.00（-4.92～-0.45）0.003
AAPC1990—2023年-1.04（-1.14～-0.89）<0.001
女性APC1990—2002年-1.69（-1.89～-1.44）<0.001
2002—2014年-3.98（-4.26～-3.77）<0.001
2014—2023年-1.95（-2.25～-1.52）<0.001
AAPC1990—2023年-2.60（-2.66～-2.53）<0.001
总体APC1990—2015年-1.16（-1.60～-0.46）0.031
2015—2021年-0.40（-2.04～1.04）0.544
2021—2023年-2.94（-4.58～-0.68）<0.001
AAPC1990—2023年-1.13（-1.21～-0.99）<0.001
), ArticleFig(id=1311350207816761351, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350191328953288, language=CN, label=表1, caption=

1990—2023年中国归因于吸烟的白血病疾病负担的年度变化情况

, figureFileSmall=null, figureFileBig=null, tableContent=
指标分类具体指标时间变化值（95%CI）（%）P值
标化死亡率（ASMR）男性APC1990—2007年-1.03（-2.12～-0.79）0.042
2007—2023年-0.71（-0.91～0.29）0.088
AAPC1990—2023年-0.87（-0.98～-0.76）<0.001
女性APC1990—2002年-1.15（-1.35～-0.90）<0.001
2002—2014年-4.06（-4.35～-3.84）<0.001
2014—2023年-1.77（-2.07～-1.38）<0.001
AAPC1990—2023年-2.38（-2.45～-2.32）<0.001
总体APC1990—2018年-0.92（-1.99～0.27）0.069
2018—2021年0.24（-1.87～1.12）0.933
2021—2023年-3.46（-5.33～-0.62）0.003
AAPC1990—2023年-0.97（-1.08～-0.81）<0.001
标化DALY率（ASDR）男性APC1990—2015年-1.10（-1.32～-0.37）0.036
2015—2021年-0.12（-1.95～1.43）0.965
2021—2023年-3.00（-4.92～-0.45）0.003
AAPC1990—2023年-1.04（-1.14～-0.89）<0.001
女性APC1990—2002年-1.69（-1.89～-1.44）<0.001
2002—2014年-3.98（-4.26～-3.77）<0.001
2014—2023年-1.95（-2.25～-1.52）<0.001
AAPC1990—2023年-2.60（-2.66～-2.53）<0.001
总体APC1990—2015年-1.16（-1.60～-0.46）0.031
2015—2021年-0.40（-2.04～1.04）0.544
2021—2023年-2.94（-4.58～-0.68）<0.001
AAPC1990—2023年-1.13（-1.21～-0.99）<0.001
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1990—2023年中国归因于吸烟的白血病疾病负担分析
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杨文正 , 曾智 , 于凯明 , 肖舒雯 , 杨添皓 , 孙倩文
现代预防医学 | 疾病预防控制 2026,53(14): 2656-2661
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现代预防医学 |疾病预防控制 2026 , 53 (14) : 2656 -2661
1990—2023年中国归因于吸烟的白血病疾病负担分析
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杨文正, 曾智 , 于凯明, 肖舒雯, 杨添皓, 孙倩文
作者信息
  • 南京中医药大学卫生经济管理学院，江苏 南京 210023
通讯作者:
曾智，E-mail：
作者简介:

杨文正（2003—），男，硕士在读，研究方向：卫生政策与管理

Disease burden of leukemia attributable to smoking, China, 1990-2023
Wen-zheng YANG, Zhi ZENG , Kai-ming YU, Shu-wen XIAO, Tian-hao YANG, Qian-wen SUN
Affiliations
  • School of Health Economics and Management, Nanjing University of Traditional Chinese Medicine, Nanjing, Jiangsu 210023, China
出版时间: 2026-07-25 doi: 10.20043/j.cnki.MPM.202601180
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摘要
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目的

分析1990—2023年中国归因于吸烟的白血病负担趋势及驱动因素，为防控策略提供依据。

方法

基于2023年全球疾病负担数据库，提取中国归因于吸烟的白血病死亡和伤残调整寿命年（DALY）数据。采用Joinpoint回归模型分析标化率的时间变化趋势，利用分解分析法探究人口增长、老龄化及流行病学变化对疾病负担的影响。

结果

1990—2023年，中国归因于吸烟的白血病死亡人数从0.42万例增至0.82万例（增长96.82%），DALY从11.83万人年增至20.36万人年（增长72.13%）。标化死亡率（age-standardized mortality rate,ASMR）和标化DALY率（age-standardized DALY rate,ASDR）呈下降趋势（AAPC分别为-0.97%和-1.13%，P<0.001）。分解分析显示，人口增长和老龄化是导致疾病负担绝对值增加的主要驱动力。

结论

1990—2023年中国归因于吸烟的白血病标化疾病负担虽呈下降趋势，但受人口老龄化等因素影响，绝对负担仍持续加重且存在显著的性别差异。男性和老年人群是防控重点，需进一步强化控烟干预以遏制负担增长。

白血病  /  吸烟  /  疾病负担  /  Joinpoint回归  /  分解分析
Objective

To analyze the temporal trends and driving factors of the burden of leukemia attributable to smoking in China from 1990 to 2023, and to provide evidence for prevention and control strategies.

Methods

Based on the Global Burden of Disease Study 2023 database, data on leukemia deaths and disability-adjusted life years (DALYs) attributable to smoking in China were extracted. The Joinpoint regression model was used to analyze the temporal trends of standardized rates. Decomposition analysis was employed to explore the impacts of population growth, aging, and epidemiological changes on the disease burden.

Results

From 1990 to 2023, the number of leukemia deaths attributable to smoking in China increased from 4 200 to 8 200 (an increase of 96.82%), and DALYs increased from 118 300 to 203 600 person-years (an increase of 72.13%). The age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR) showed downward trends (with average annual percent changes of -0.97% and -1.13%, respectively, P<0.001). Decomposition analysis indicated that population growth and aging were the main driving forces for the increase in the absolute value of the disease burden.

Conclusion

Although the age-standardized burden of leukemia attributable to smoking in China showed a declining trend from 1990 to 2023, the absolute burden continued to increase under the influence of factors such as population aging, and significant sex disparities were observed. Males and older adults should be prioritized in prevention and control efforts, and tobacco control interventions should be further strengthened to curb the growing burden.

Leukemia  /  Smoking  /  Disease burden  /  Joinpoint regression  /  Decomposition analysis
杨文正, 曾智, 于凯明, 肖舒雯, 杨添皓, 孙倩文. 1990—2023年中国归因于吸烟的白血病疾病负担分析. 现代预防医学, 2026 , 53 (14) : 2656 -2661 . DOI: 10.20043/j.cnki.MPM.202601180
Wen-zheng YANG, Zhi ZENG, Kai-ming YU, Shu-wen XIAO, Tian-hao YANG, Qian-wen SUN. Disease burden of leukemia attributable to smoking, China, 1990-2023[J]. Modern Preventive Medicine, 2026 , 53 (14) : 2656 -2661 . DOI: 10.20043/j.cnki.MPM.202601180
正文
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白血病作为一类高度异质性的血液系统恶性肿瘤，因其高致死率和复杂的病因，已成为全球公共卫生领域的重大挑战[1]。流行病学统计显示，2022年白血病已跃升为全球第二大血液系统恶性肿瘤[2]。在中国，这一疾病负担尤为沉重，尽管特定亚型的生存率有所提升，但许多地区的发病率仍呈上升态势[3]。尽管总体死亡率呈下降趋势，但伤残调整生命年（disability-adjusted life year,DALY）持续处于高位[4]。作为综合衡量早死与伤残所致健康寿命损失的重要指标，DALY持续高位表明白血病对患者生命质量和预期寿命的双重损害仍较为突出，同时也提示其医疗需求、家庭压力及社会疾病负担尚未明显缓解，因此疾病防控形势依然严峻。
目前吸烟诱发白血病的生物学机制已得到阐释，特别是其与急性髓系白血病发病风险的密切关联已被证实[5]。作为全球最大的烟草消费国，中国面临严峻的烟草相关疾病负担[6]。研究表明，吸烟的健康危害具有长期累积效应，吸烟归因的白血病负担水平随年龄增长而显著攀升[7]。目前国内关于吸烟与白血病的研究主要集中于两个方面：一是探讨吸烟暴露与白血病发生风险之间的关联[8]，二是分析白血病患者持续吸烟对生存结局的不良影响[9]。总体而言，现有研究多停留在相关性或个体预后层面，缺乏基于全国性数据对中国人群归因于吸烟的白血病疾病负担开展长时间跨度的系统评估。基于此，本研究利用全球疾病负担（Global Burden of Disease, GBD）数据库，提取1990—2023年中国人群归因于吸烟的白血病相关数据，对中国归因于吸烟的白血病疾病负担进行系统分析，并对其变化趋势及人口增长、人口老龄化和流行病学变化驱动作用进行量化分析，以期弥补现有研究不足，为白血病防控策略制定和卫生资源配置提供依据。
1　资料与方法
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1.1　数据来源
本研究的数据源自2023年全球疾病负担（GBD 2023）数据库[10]。筛选研究变量如下：地区选择“China”，死亡原因选择“Leukemia”，风险因素选择“Smoking”，指标选择“DALYs”“Deaths”。年龄组选择30～34、35～39、40～44、45～49、50～54、55～59、60～64、65～69、70～74、75～79、80～84、85～89、90～94和≥95岁（数据库显示30岁以下人群无吸烟归因负担）。
根据GBD 2023的疾病分类体系，Leukemia属于第3层级疾病类别，为白血病总体类别，包含急性淋巴细胞白血病、慢性淋巴细胞白血病、急性髓系白血病、慢性髓系白血病及其他白血病等亚型，对应ICD-10编码范围为C91-C95.9[11]。Smoking为第3层级风险因素，主要指对可燃烟草制品的主动吸烟暴露，通常包括当前吸烟者和既往吸烟者（其分类与界定依据GBD风险暴露估计框架）。其中，当前吸烟者包括每日吸烟和非每日吸烟人群，既往吸烟者一般指已停止使用所有吸烟型烟草制品至少6个月者。对吸烟暴露的量化除暴露状态外，还综合考虑每日吸烟量、累计吸烟年限以及戒烟时长等指标，以反映暴露剂量和暴露持续时间[12]。
本研究中用于评估中国归因于吸烟的白血病疾病负担的指标包括死亡人数、DALYs、年龄标化死亡率（age-standardized mortality rate，ASMR）以及年龄标化DALY率（age-standardized DALY rate，ASDR）以及对应的95%不确定性区间（uncertainty interval，UI）。其中DALY的基本含义是从发病到死亡所损失的寿命年。该指标由早逝损失寿命年（YLL）和伤残损失寿命年（YLD）两部分组成[13]。
1.2　研究方法
1.2.1　Joinpoint回归模型
为探究1990-2023年间中国归因于吸烟的白血病疾病负担时间变化趋势，采用Joinpoint回归对年龄标化率进行分段回归拟合[14]。模型以年份为自变量，以率的自然对数为因变量，设置拐点数在预设范围内变化，采用蒙特卡罗置换法进行模型比较与拐点筛选，选择拟合最优且具有统计学意义的模型[15]。并计算相应指标的年度变化百分比（annual percentage change, APC）、平均年度变化百分比（average annual percentage change, AAPC）及其95%置信区间（confidence interval, CI），检验水准α=0.05。
1.2.2　分解分析
本研究采用Das Gupta提出的分解分析法量化人口增长、人口老龄化以及流行病学变化三种因素对中国归因于吸烟的白血病疾病负担的相对影响，该方法的核心原理是将疾病负担绝对指标（如死亡人数或 DALYs）在时间维度上的总变化量，数学分解为若干个影响因子的独立贡献之和[16]。具体而言，某一特定年份的疾病负担总量（E）可表示为总人口数（P）、各年龄组人口结构占比（A，反映人口老龄化因素）以及各年龄组特定疾病负担率（R，反映流行病学变化因素）的函数，即E=f（P,A,R）。以1990年和2023年为比较时点，在保持其余因素不变的条件下，人口增长效应表示仅由总人口规模变化所导致的疾病负担变化；人口老龄化效应表示仅由年龄结构向高龄组转移所导致的疾病负担变化；流行病学变化效应表示在扣除总人口规模和年龄结构变化后，由各年龄组疾病负担率变化所导致的疾病负担变化[17]。在分解分析图中，黑点代表三种因素导致的疾病负担总和，正值（负值）指该因素对疾病负担增加有正向（负向）影响。
1.3　统计分析
本研究运用R 4.5.2软件对1990—2023年中国归因于吸烟的白血病的死亡、DALY率等相关数据进行统计分析。运用joinpoint 5.2.0软件构建joinpoint模型，分析归因于吸烟的白血病疾病负担变化趋势，并运用分解分析法探究人口增长、人口老龄化以及流行病学变化对白血病疾病负担的相对影响。
2　结果
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2.1　1990—2023年中国归因于吸烟的白血病疾病负担变化情况
从1990到2023年，由于吸烟引起的白血病死亡人数在中国从0.42万人增加到0.82万人，增长幅度达96.82%。
ASMR由0.49/10万下降至0.35/10万，降低了28.43%。AAPC值为-0.97%（95%CI：-1.08～-0.81，P<0.001）。其中，ASMR在1990—2018年（APC=-0.92%，P＝0.069）和2018—2021年（APC=0.24%，P>0.05）期间无明显变化，2021—2023年（APC=-3.46%，P<0.05）呈现显著下降趋势。
DALYs由11.83万人年上升至20.36万人年，增长了72.13%。ASDR由12.82/10万下降至8.73/10万，降低了31.92%，AAPC值为-1.13%（95%CI：-1.21～-0.99，P<0.001），其中，1990—2015年（APC=-1.16%，P<0.05）和2021—2023年（APC＝-2.94%，P<0.001）呈显著下降趋势，2015—2021年间趋势趋于稳定（APC=-0.40%，P=0.544）。
1990—2023年中国女性归因于吸烟的白血病ASMR呈下降趋势，AAPC为-2.38%（95%CI：-2.45～-2.32，P<0.001），其中，1990—2002年（APC=-1.15%，P<0.05）、2002—2014年（APC=-4.06%，P<0.05）和2014—2023年（APC=-1.77%，P<0.05）三个分段均呈显著下降趋势；男性的AAPC为-0.87%（95%CI：-0.98～-0.76，P<0.001），仅在1990—2007年呈显著下降（APC=-1.03%，P<0.05）。1990—2023年中国女性归因于吸烟的白血病的ASDR呈下降趋势，AAPC为-2.60%（95%CI：-2.66～-2.53，P<0.001）；男性的AAPC为-1.04%（95%CI：-1.14～-0.89，P<0.001），在1990—2015年（APC=-1.10%，P<0.05）和2021—2023年（APC=-3.00%，P<0.05）呈显著下降趋势。表1、图1~2。
2.2　不同年龄组归因于吸烟的白血病疾病负担变化趋势
1990—2023年中国归因于吸烟的白血病疾病负担随年龄增长呈先升后降的趋势。以2023年为例，30～34岁年轻人群的疾病负担处于最低水平，死亡率和DALY率分别为0.05/10万和2.84/10万；随后随着年龄增长负担迅速加重，DALY率在70～74岁组达到峰值（55.43/10万），死亡率在75～79岁组达到峰值（3.19/10万）；跨过峰值年龄段后，两项负担指标随之快速回落，至最高龄组（≥95岁组）时，死亡率和DALY率分别显著下降至0.86/10万和7.10/10万。如图3。
2.3　归因于吸烟的白血病疾病负担变化的分解分析
人口增长（98.56%）和老龄化（56.94%）是死亡人数增加的主要驱动力，而流行病学变化（-55.50%）则起抑制作用。DALYs的分解结果与死亡趋势保持一致。人口增长仍是总体负担上升的首要驱动力（123.53%），老龄化次之（53.14%），流行病学变化则产生相反的影响（-76.67%）。就性别而言，男性的死亡负担净增值远高于女性；且流行病学改善的抵消作用在女性中更为强烈（-351.74%），导致女性总体增幅极小，如图4。
3　讨论
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本研究系统评估了1990—2023年中国归因于吸烟的白血病疾病负担。研究发现，在此期间归因于吸烟的白血病ASMR和ASDR分别下降了28.43%和31.92%，但死亡人数和DALYs分别增加了96.82%和72.13%。ASMR和ASDR的下降得益于中国血液肿瘤诊疗水平的飞跃以及支持治疗条件的改善，显著延长了白血病患者的生存期[18]。ASMR在2021—2023年间呈现出更为显著的下降趋势。这一积极变化可能与近年来中国政府强力推进《“健康中国2030”规划纲要》，实施一系列癌症防治计划有关，全民健康素养的提升和早诊早治观念的普及在其中起到了推动作用[19]。此外，2021—2023年指标的显著下降可能与COVID-19作为竞争死因有关，部分高危患者可能因新冠提前死亡，导致白血病死亡率统计性下降[20]。然而，绝对负担的增长表明，临床进步不足以抵消人口增长和老龄化带来的负面影响，吸烟作为白血病主要的可预防危险因素，其对中国成年人群健康的威胁形势依然严峻[21]。而标化YLD率的上升提示白血病负担由早死向致残转移。随着靶向治疗等进步，患者生存期延长，但治疗相关毒性与功能损害使带病生存负担增加[22]。
性别差异方面，1990—2023年间，女性ASMR和ASDR的下降速度显著快于男性，提示男性归因于吸烟的白血病疾病负担更重。至2023年，男性归因于吸烟的白血病死亡人数和DALYs分别约为女性的26倍和29倍，这种差别一方面源于中国两性吸烟率的悬殊差异。调查显示，男性吸烟率处于较高水平，而女性吸烟率始终维持在较低水平。以2024年全国调查为例，男性吸烟率为43.9%，女性为1.8%[23]。另一方面，男性人群中重度吸烟者比例较高、烟草依赖程度较强、戒烟难度较大，也可能进一步增加其累积吸烟暴露水平，从而加重归因于吸烟的白血病疾病负担[24]。针对男性高流行及重度吸烟特征，应结合无烟环境建设，普及个体化的戒烟门诊与行为干预，从源头降低烟草累积暴露风险。
年龄差异方面，从1990至2023年，疾病负担随年龄增长呈先升后降的趋势，DALY率在70～74岁组达到峰值，死亡率在75～79岁组达到峰值，总体表现为70～79岁阶段负担最重。这可能与免疫衰老有关，即老年期免疫监视功能下降增加了肿瘤发生与死亡风险[25]。此外，还可能与共病累积、衰弱状态及治疗耐受性下降相关。老年白血病患者常同时患有心血管疾病、糖尿病和肾功能减退等慢性病，同时对强化治疗方案的耐受性较差，这些因素可能增加并发症和死亡风险，从而进一步加重高龄组疾病负担[26]。这提示着在关注特定高危因素的同时，针对老年人群的白血病综合防控与管理已迫在眉睫[27]。针对高龄群体，建议依托基层公卫网络，将白血病早期预警指标纳入常规防癌体检与慢病筛查，实施精准的个体化多病共管。
分解分析表明，人口增长是推高中国归因于吸烟的白血病负担的首要驱动因素，其次是人口老龄化；而流行病学变化，即在扣除了人口增长和人口老龄化之后，由疾病发生规律本身的变化所带来的那部分健康结局变化，则起到了关键的抑制作用。随着中国老龄化程度的加深，未来的白血病防控策略必须适应人口结构的变化，从单纯的临床治疗向全生命周期的健康管理转变，特别是要关注老龄化背景下的共病管理和生活质量提升[28]。总体防控需响应《健康中国2030》战略，推动公共卫生资源向上述重点人群前移，实现由疾病治疗向全生命周期健康管理的精准转型[19]。
本研究也存在一定的局限性。首先，GBD数据基于多源数据建模估算，GBD显示30岁前归因于吸烟的白血病负担近似为0，并不意味着真实世界完全为零。其次，研究未区分白血病的具体亚型，混合分析可能掩盖吸烟对特定高危亚型的特异性影响[29]。最后，本研究主要关注吸烟这一危险因素，未纳入环境暴露、职业防护等其他潜在混杂因素的联合作用，未来的研究可进一步细化多重风险因素的交互影响。
综上所述，1990—2023年间，中国归因于吸烟的白血病标化疾病负担虽呈显著下降趋势，这反映了诊疗技术的进步与流行病学改善，但受人口增长与人口老龄化的双重驱动，疾病负担绝对值仍显著增加。此外，疾病负担分布特征具有高度异质性，不仅存在巨大的性别差异，男性负担远高于女性，且高龄人群负担最重，同时整体负担正逐渐由早逝向致残转移，表现为伤残损失寿命年上升。应采取控烟为主、早筛为辅、老龄化应对并重的综合策略，以有效遏制这一可预防的疾病负担。
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2026年第53卷第14期
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doi: 10.20043/j.cnki.MPM.202601180
  • 接收时间：2026-01-12
  • 首发时间：2026-09-28
  • 出版时间：2026-07-25
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  • 收稿日期：2026-01-12
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国家自然科学基金青年科学基金项目(72504145)
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    南京中医药大学卫生经济管理学院，江苏 南京 210023

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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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