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Article(id=1324078416680591654, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202508408, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1756137600000, receivedDateStr=2025-08-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614494723, onlineDateStr=2026-11-02, pubDate=1767974400000, pubDateStr=2026-01-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614494723, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614494723, creator=13701087609, updateTime=1793614494723, updator=13701087609, issue=Issue{id=1324078333767594037, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='1', pageStart='1', pageEnd='192', issueExtLink='null', onlineDate='null', pubDate='1767974400000', pubDateStr='2026-01-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614474956, creator='13701087609', updateTime=1793614571752, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078739914621270, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078739914621271, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=20, endPage=25, ext={EN=ArticleExt(id=1324078417087439143, articleId=1324078416680591654, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Age-period-cohort analysis of the burden of cervical cancer attributable to smoking in China from 1990 to 2021, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the trends in the burden of cervical cancer attributable to smoking in China from 1990 to 2021, and to explore the disease burden patterns across regions with different Socio-demographic Index (SDI) levels, thereby providing a scientific basis for formulating targeted tobacco control measures and cervical cancer prevention strategies.

Methods

Based on data from the Global Burden of Disease (GBD) Study 2021, mortality and disability-adjusted life year(DALY) rates of cervical cancer attributable to smoking in China and five SDI regions among individuals aged 25-94 years were extracted. Joinpoint regression was used to analyze the temporal trends in age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR). The Age-Period-Cohort (APC) model was employed to assess age, period, and cohort effects.

Results

From 1990 to 2021, both the ASMR and ASDR of cervical cancer attributable to smoking in China decreased significantly, with average annual percentage changes (AAPCs) of -2.177% (95% CI: -2.592~-1.759) and -2.054% (95% CI:-2.280~-1.826), respectively. The overall burden in China remained consistently lower than the average of its corresponding SDI region. Regional comparisons revealed that the largest decline in mortality occurred in the middle SDI region (AAPC=-2.874%), while the fastest decline in ASDR was observed in the low SDI region (AAPC=-2.863%). The high SDI region showed the smallest declines for both metrics. In China, age-specific analyses showed that the most pronounced declines in ASMR for cervical cancer attributable to smoking were observed in the 70-74 and ≥95 years age groups. The ASDR exhibited a unimodal distribution with age, peaking at 57 years, and showed the largest decline in the 70-74 years age group. However, the disease burden in the 30-59 years age group still showed an increasing trend in some SDI regions. APC model analysis further indicated net drifts of -0.540% for ASMR and -1.946% for ASDR. Both period and cohort effects decreased significantly, with the cohort effect being the most prominent, showing an 82.97% reduction in the risk of DALY rates attributable to smoking from the 1895 to the 1990 birth cohorts.

Conclusion

From 1990 to 2021, the burden of cervical cancer attributable to smoking in China showed a significant overall decline, but with notable regional and age heterogeneities. Substantial improvements were observed in low and middle-high SDI regions and among older age groups, while the burden in young and middle-aged populations increased in some regions. Future prevention and control efforts should focus on the young and middle-aged population and promote tailored strategies across different regions.

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目的

分析中国1990—2021年归因于吸烟的宫颈癌疾病负担变化趋势，探究不同社会人口指数（socio-demographic index, SDI）地区的疾病负担发展模式，为制定针对性的控烟措施和宫颈癌防控策略提供科学参考。

方法

基于全球疾病负担2021年数据，提取中国及五类SDI地区25～94岁人群归因于吸烟的宫颈癌死亡率、伤残调整寿命年（disability-adjusted life year,DALY）率等数据；采用joinpoint回归分析年龄标准化死亡率（age-standardized mortality rate，ASMR）和年龄标化DALY率（age-standardized DALYs rate,ASDR）的时间趋势，年龄-时期-队列模型分析年龄、时期和队列效应。

结果

1990—2021年，中国归因于吸烟的宫颈癌ASMR与ASDR均显著下降，平均年度变化百分比(average annual percentage change,AAPC)分别为-2.177%（-2.592～-1.759）与-2.054%（-2.280～-1.826），且整体负担持续低于同类SDI地区。地区比较显示，死亡降幅在中等SDI地区最大（AAPC=-2.874%），而ASDR在低SDI地区下降最快（AAPC=-2.863%），高SDI地区两项指标降幅均为最小。在中国，年龄别分析揭示，归因于吸烟的宫颈癌ASMR在70～74岁及95岁以上年龄组下降最为显著；而其ASDR随年龄增长呈单峰分布，于57岁达到峰值，并在70～74岁年龄段降幅最大。然而，30～59岁中青年人群的疾病负担在部分SDI地区仍呈现上升趋势。年龄-时期-队列模型进一步显示，其ASMR与ASDR的净漂移分别为-0.540%与-1.946%，时期效应与队列效应均显著减弱，其中队列效应降幅最为突出，归因于吸烟的宫颈癌DALY率风险自1895年至1990年下降82.97%。

结论

1990—2021年，中国归因于吸烟的宫颈癌疾病负担呈现显著下降，但存在明显的地区与年龄差异性。低与中高SDI地区及高龄组改善显著，而中青年群体在部分地区负担仍呈上升趋势。未来防控应聚焦中青年人群，并推进地区差异化的精准策略。

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郝海亚（1993—），女，硕士在读，研究方向：疾病预防与控制研究

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李树林，E-mail:
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注：ASMR为年龄标准化死亡率；ASDR年龄标准化DALY率。

, figureFileSmall=gTUYpO++x3B8HvBnurDxaw==, figureFileBig=fgAX0J3fJEUtp+sXuunJBA==, tableContent=null), ArticleFig(id=1324078421789253981, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078416680591654, language=EN, label=Figure 4, caption=Age-period-cohort model of age-standardized mortality risk of cervical cancer attributable to smoking, figureFileSmall=Gmuq+2emUPdLRfbFycLYXQ==, figureFileBig=Te78VUBiAsNo8gbmPn+/vQ==, tableContent=null), ArticleFig(id=1324078421856362846, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078416680591654, language=CN, label=图4, caption=归因于吸烟的宫颈癌ASMR风险APC模型, figureFileSmall=Gmuq+2emUPdLRfbFycLYXQ==, figureFileBig=Te78VUBiAsNo8gbmPn+/vQ==, tableContent=null), ArticleFig(id=1324078421931860319, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078416680591654, language=EN, label=Figure 5, caption=Age-period-cohort model of age-standardized DALY risk of cervical cancer attributable to smoking, figureFileSmall=pYqvZ7+WHEQB0k7DUo9qAQ==, figureFileBig=GLJUQTiPOlmrepNRBGCABQ==, tableContent=null), ArticleFig(id=1324078422007357792, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078416680591654, language=CN, label=图5, caption=归因于吸烟的宫颈癌ASDR风险APC模型

注：ASMR为年龄标准化死亡率；ASDR为年龄标准化DALY率。

, figureFileSmall=pYqvZ7+WHEQB0k7DUo9qAQ==, figureFileBig=GLJUQTiPOlmrepNRBGCABQ==, tableContent=null), ArticleFig(id=1324078422087049569, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078416680591654, language=EN, label=Table 1, caption=

Average annual percent change in the burden of cervical cancer attributable to smoking

, figureFileSmall=null, figureFileBig=null, tableContent=
项目地区AAPC95%CIt值P值
死亡率中国-2.177-2.592～-1.759-10.131<0.001
高SDI-2.739-2.816～-2.662-68.840<0.001
高-中SDI-1.397-1.563～-1.230-16.332<0.001
中SDI-2.874-3.007～-2.741-41.639<0.001
中-低SDI-2.281-2.347～-2.214-66.276<0.001
低SDI-2.108-2.238～-1.978-31.393<0.001
DALY率中国-2.054-2.280～-1.826-17.543<0.001
高SDI-1.408-1.588～-1.229-15.271<0.001
高-中SDI-2.758-2.838～-2.677-66.212<0.001
中SDI-2.453-2.570～-2.336-40.451<0.001
中-低SDI-2.324-2.423～-2.225-45.487<0.001
低SDI-2.863-3.040～-2.686-31.295<0.001
), ArticleFig(id=1324078423773159780, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078416680591654, language=CN, label=表1, caption=

归因于吸烟的宫颈癌疾病负担平均年度变化百分比

, figureFileSmall=null, figureFileBig=null, tableContent=
项目地区AAPC95%CIt值P值
死亡率中国-2.177-2.592～-1.759-10.131<0.001
高SDI-2.739-2.816～-2.662-68.840<0.001
高-中SDI-1.397-1.563～-1.230-16.332<0.001
中SDI-2.874-3.007～-2.741-41.639<0.001
中-低SDI-2.281-2.347～-2.214-66.276<0.001
低SDI-2.108-2.238～-1.978-31.393<0.001
DALY率中国-2.054-2.280～-1.826-17.543<0.001
高SDI-1.408-1.588～-1.229-15.271<0.001
高-中SDI-2.758-2.838～-2.677-66.212<0.001
中SDI-2.453-2.570～-2.336-40.451<0.001
中-低SDI-2.324-2.423～-2.225-45.487<0.001
低SDI-2.863-3.040～-2.686-31.295<0.001
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1990—2021年归因于吸烟的中国宫颈癌疾病负担的年龄-时期-队列分析
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郝海亚 1 , 李树林 1, 2 , 李翡 3 , 黄冕 1
现代预防医学 | 流行病与统计方法 2026,53(1): 20-25
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现代预防医学 |流行病与统计方法 2026 , 53 (1) : 20 -25
1990—2021年归因于吸烟的中国宫颈癌疾病负担的年龄-时期-队列分析
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郝海亚1, 李树林1, 2 , 李翡3, 黄冕1
作者信息
  • 1.新疆医科大学公共卫生学院，新疆 乌鲁木齐 830011
  • 2.乌鲁木齐市第一人民医院公共卫生科，新疆 乌鲁木齐 830002
  • 3.陕西中医药大学第一临床医学院
通讯作者:
李树林，E-mail:
作者简介:

郝海亚（1993—），女，硕士在读，研究方向：疾病预防与控制研究

Age-period-cohort analysis of the burden of cervical cancer attributable to smoking in China from 1990 to 2021
Hai-ya HAO1, Shu-lin LI1, 2 , Fei LI3, Mian HUANG1
Affiliations
  • School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region 830011, china
出版时间: 2026-01-10 doi: 10.20043/j.cnki.MPM.202508408
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摘要
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目的

分析中国1990—2021年归因于吸烟的宫颈癌疾病负担变化趋势，探究不同社会人口指数（socio-demographic index, SDI）地区的疾病负担发展模式，为制定针对性的控烟措施和宫颈癌防控策略提供科学参考。

方法

基于全球疾病负担2021年数据，提取中国及五类SDI地区25～94岁人群归因于吸烟的宫颈癌死亡率、伤残调整寿命年（disability-adjusted life year,DALY）率等数据；采用joinpoint回归分析年龄标准化死亡率（age-standardized mortality rate，ASMR）和年龄标化DALY率（age-standardized DALYs rate,ASDR）的时间趋势，年龄-时期-队列模型分析年龄、时期和队列效应。

结果

1990—2021年，中国归因于吸烟的宫颈癌ASMR与ASDR均显著下降，平均年度变化百分比(average annual percentage change,AAPC)分别为-2.177%（-2.592～-1.759）与-2.054%（-2.280～-1.826），且整体负担持续低于同类SDI地区。地区比较显示，死亡降幅在中等SDI地区最大（AAPC=-2.874%），而ASDR在低SDI地区下降最快（AAPC=-2.863%），高SDI地区两项指标降幅均为最小。在中国，年龄别分析揭示，归因于吸烟的宫颈癌ASMR在70～74岁及95岁以上年龄组下降最为显著；而其ASDR随年龄增长呈单峰分布，于57岁达到峰值，并在70～74岁年龄段降幅最大。然而，30～59岁中青年人群的疾病负担在部分SDI地区仍呈现上升趋势。年龄-时期-队列模型进一步显示，其ASMR与ASDR的净漂移分别为-0.540%与-1.946%，时期效应与队列效应均显著减弱，其中队列效应降幅最为突出，归因于吸烟的宫颈癌DALY率风险自1895年至1990年下降82.97%。

结论

1990—2021年，中国归因于吸烟的宫颈癌疾病负担呈现显著下降，但存在明显的地区与年龄差异性。低与中高SDI地区及高龄组改善显著，而中青年群体在部分地区负担仍呈上升趋势。未来防控应聚焦中青年人群，并推进地区差异化的精准策略。

1990—2021年  /  宫颈癌  /  疾病负担  /  年龄-时期-队列分析
Objective

To analyze the trends in the burden of cervical cancer attributable to smoking in China from 1990 to 2021, and to explore the disease burden patterns across regions with different Socio-demographic Index (SDI) levels, thereby providing a scientific basis for formulating targeted tobacco control measures and cervical cancer prevention strategies.

Methods

Based on data from the Global Burden of Disease (GBD) Study 2021, mortality and disability-adjusted life year(DALY) rates of cervical cancer attributable to smoking in China and five SDI regions among individuals aged 25-94 years were extracted. Joinpoint regression was used to analyze the temporal trends in age-standardized mortality rate (ASMR) and age-standardized DALY rate (ASDR). The Age-Period-Cohort (APC) model was employed to assess age, period, and cohort effects.

Results

From 1990 to 2021, both the ASMR and ASDR of cervical cancer attributable to smoking in China decreased significantly, with average annual percentage changes (AAPCs) of -2.177% (95% CI: -2.592~-1.759) and -2.054% (95% CI:-2.280~-1.826), respectively. The overall burden in China remained consistently lower than the average of its corresponding SDI region. Regional comparisons revealed that the largest decline in mortality occurred in the middle SDI region (AAPC=-2.874%), while the fastest decline in ASDR was observed in the low SDI region (AAPC=-2.863%). The high SDI region showed the smallest declines for both metrics. In China, age-specific analyses showed that the most pronounced declines in ASMR for cervical cancer attributable to smoking were observed in the 70-74 and ≥95 years age groups. The ASDR exhibited a unimodal distribution with age, peaking at 57 years, and showed the largest decline in the 70-74 years age group. However, the disease burden in the 30-59 years age group still showed an increasing trend in some SDI regions. APC model analysis further indicated net drifts of -0.540% for ASMR and -1.946% for ASDR. Both period and cohort effects decreased significantly, with the cohort effect being the most prominent, showing an 82.97% reduction in the risk of DALY rates attributable to smoking from the 1895 to the 1990 birth cohorts.

Conclusion

From 1990 to 2021, the burden of cervical cancer attributable to smoking in China showed a significant overall decline, but with notable regional and age heterogeneities. Substantial improvements were observed in low and middle-high SDI regions and among older age groups, while the burden in young and middle-aged populations increased in some regions. Future prevention and control efforts should focus on the young and middle-aged population and promote tailored strategies across different regions.

1990—2021  /  Cervical cancer  /  Disease burden  /  Age-period-cohort analysis
郝海亚, 李树林, 李翡, 黄冕. 1990—2021年归因于吸烟的中国宫颈癌疾病负担的年龄-时期-队列分析. 现代预防医学, 2026 , 53 (1) : 20 -25 . DOI: 10.20043/j.cnki.MPM.202508408
Hai-ya HAO, Shu-lin LI, Fei LI, Mian HUANG. Age-period-cohort analysis of the burden of cervical cancer attributable to smoking in China from 1990 to 2021[J]. Modern Preventive Medicine, 2026 , 53 (1) : 20 -25 . DOI: 10.20043/j.cnki.MPM.202508408
正文
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宫颈癌（cervical cancer）是女性恶性肿瘤之一，也是导致女性癌症相关死亡的重要原因[1]。在我国，宫颈癌的发病与死亡形势严峻，2021年宫颈癌发病人数和死亡人数分别为13.37万人和4.64万人，严重威胁女性健康，给家庭和社会带来沉重的疾病负担[2]。
吸烟作为一种明确的致癌危险因素，与宫颈癌的发生发展密切相关,烟草烟雾中含有多环芳烃、尼古丁等多种有害物质，可通过影响宫颈细胞DNA修复、促进人乳头瘤病毒持续感染等机制，增加宫颈癌的发病风险[3]。研究显示，吸烟史超过10年，每天吸烟超过15支的女性发生宫颈癌的风险为80%，是宫颈癌的重要诱因之一[4]。
疾病的疾病负担也存在明显的地区差异，不同水平地区的宫颈癌负担存在差异[5]。而社会人口指数（socio-demographic index, SDI）作为综合反映地区经济、教育水平的指标，可能在一定程度上影响吸烟相关宫颈癌的疾病负担模式。目前，虽有学者对吸烟与宫颈癌的关联进行过研究[6-7]，但结合SDI差异系统分析归因于吸烟的中国宫颈癌疾病负担及其变化趋势的研究仍较为缺乏。本研究基于全球疾病负担研究2021（Global Burden of Disease Study 2021, GBD 2021）结果，提取1990—2021年中国和五类SDI地区归因于吸烟的宫颈癌死亡和伤残调整寿命年（disability-adjusted life years,DALYs）相关数据，分析其疾病负担及变化趋势，探究不同SDI地区的疾病负担发展模式，为制定针对性的控烟措施和宫颈癌防控策略提供科学参考。
1　资料与方法
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1.1　数据来源
本研究数据来源于GBD 2021全球健康数据交换数据库(https://vizhub.healthdata.org/gbd-results/)，提取1990—2021年中国和五类SDI地区25～94岁人群归因于吸烟的宫颈癌死亡和DALYs相关数据进行分析。此外，GBD研究采用比较风险评估框架，通过理论最小风险暴露水平、综合多元回归和调解分析等方法，估算了吸烟独立于其他宫颈癌危险因素（如HPV感染、口服避孕药等）的人群归因分值（population attributable fraction,PAF）和归因负担。因此，本研究使用的数据代表的是排除了其他主要风险因素混杂后，可归因于吸烟的疾病负担[8]。
SDI是基于人均收入水平、平均受教育年限和总和生育率三项核心指标构建的综合指数，用以量化国家或地区的社会发展水平。其计算过程包括对各指标进行标准化处理，并计算其几何平均值，最终SDI值介于0～1之间，数值越高代表发展水平越高。依据SDI得分，所有国家和地区被划分为五个等级：低、中低、中、中高及高SDI地区。该五分位划分法被广泛应用于全球疾病负担研究中，以分析疾病分布与社会经济发展水平之间的关联[8]。
1.2　结局定义
GBD研究遵循比较风险评估框架，利用反事实分析理论来量化特定风险因素（此处为吸烟）导致的疾病负担。其中，吸烟暴露的定义包括目前吸烟者和既往吸烟者。目前吸烟者依据其每日吸烟的香烟当量及累积的包-年数进行评估；既往吸烟者则根据其戒烟前的吸烟状况及戒烟时长进行评估。该定义排除了目前使用咀嚼烟草、水烟以及暴露于二手烟（指非吸烟者每日吸入的、由二手烟产生的PM2.5）的个体[9]。
1.3　观察指标
本研究选取的观察指标主要包括死亡率、DALYs率，以评估归因于吸烟的宫颈癌疾病负担[10-11]。
死亡率：指在一定观察期间内，特定人群中的死亡发生频率，计算公式为（某人群某年总死亡人数/该人群同年平均人口数）×K（系数，常取100 000/10万）。
DALYs是指从发病到死亡所损失的全部健康寿命年，用于综合反映疾病从发生到死亡所导致的整体健康寿命年损失[12]。
1.4　统计学方法
使用joinpoint回归分析中国和五类不同SDI地区1990—2021年25～94岁人群归因于吸烟的宫颈癌年龄标准化死亡率(age-standardized mortality rate, ASMR)和年龄标准化DALY率(age standardized DALYs rate,ASDR)的平均年度变化百分比(annual average percentage change,AAPC)(Joinpoint软件版本5.0.2)[13-14]。为验证趋势变化的统计学意义，将AAPC与零进行比较，若P值<0.05，则认为趋势变化显著[15]。
年龄-时期-队列（age-period-cohort, APC）模型是一种多变量分析方法，基于泊松分布框架，用于分解疾病发病率或死亡率的时间趋势中年龄、时期和出生队列的独立效应[16]。本研究采用R语言（版本4.3.1）的“APC”包构建模型，通过内源估计法（intrinsic estimator, IE）解决年龄、时期和队列的共线性问题[17]。模型中：年龄效应反映不同年龄段疾病风险的生物学变化；时期效应表征外部环境（如政策、医疗技术）对全人群的即时影响；队列效应体现出生队列在生命周期中累积的社会暴露差异。
除DALY率外，本研究同步分析宫颈癌死亡率与DALY率的APC模型效应，以全面评估疾病负担驱动因素。
2　结果
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2.1　1990—2021年归因于吸烟的宫颈癌疾病负担
1990—2021年中国归因于吸烟的宫颈癌ASMR和ASDR均呈显著下降趋势。总体来看，中国全人群的ASMR和ASDR的AAPC分别为-2.177%（95% CI：-2.592%～-1.759%）和-2.054%（95% CI：-2.280%～-1.826%），见表1。五类不同SDI地区的ASMR与ASDR均表现为下降趋势，但下降幅度存在差异。ASMR在中等SDI地区降幅最大（AAPC=-2.874%），ASDR则在低SDI地区降幅最为显著（AAPC=-2.863%）。在世界范围内，中国女性宫颈癌ASMR和ASDR水平在1990—2021年始终低于中低SDI地区、中SDI地区、高-中SDI地区、高SDI地区和低SDI地区，处于同类及其他四类SDI地区之下，呈现持续下降趋势。见图1。
2.2　1990—2021年归因于吸烟的宫颈癌各年龄段疾病负担分析
在年龄别疾病负担方面，1990—2021年，中国归因于吸烟的宫颈癌ASMR随年龄增长总体呈上升趋势。与1990年相比，2021年各年龄组ASMR均有下降，其中70～74岁与95岁以上年龄组的下降幅度最为显著。对不同SDI地区而言，所有五类地区在30～59岁区间内，ASMR均呈现随年龄增长而上升的趋势。进入60～95岁以上年龄段后，高、高中、中等及中低SDI地区的ASMR增长趋于平稳，而低SDI地区则表现出无明确规律的波动性变化。
在ASDR方面，中国整体上随年龄增长呈现先上升后下降的单峰模式，且70～74岁年龄组的ASDR降幅最大。全球五类SDI地区的ASDR均表现出类似的单峰分布。在30～59岁阶段，ASDR随年龄增长而快速升高；59岁之后，其增长势头普遍减缓并转为下降。其中，中等SDI地区的ASDR随年龄变化的模式与中国最为相似。见图2、3。
2.3　1990—2021年中国归因于吸烟的宫颈癌疾病负担APC模型分析
APC模型分析结果显示，1990—2021年，中国归因于吸烟的宫颈癌ASMR其全局变化为-0.540%（95% CI: -0.641%～-0.440%），呈现小幅下降趋势。年龄效应表明，死亡风险随年龄增长而显著上升，其相对危险度（relative risk, RR）从32岁的0.036（0.030～0.043）增至97岁的1.171（0.806～1.700）。时期效应方面（以2007年为参照，RR=1），RR值从1992年的1.266（1.190～1.348）持续下降至2022年的0.700（0.659～0.744）。队列效应分析（以1945年队列为参照，RR=1）显示，出生队列的相对风险整体大幅降低，RR值从1895年队列的3.235（0.640～16.341）降至1990年队列的0.517（0.328～0.813）。
归因于吸烟的宫颈癌ASDR的APC模型各效应与死亡率变化模式相似，其全局变化为-1.946%（95% CI:-2.188%～-1.704%），下降趋势更为明显。年龄效应呈先升后降的单峰分布，RR值于57岁达到峰值23.084（21.927～24.302），后波动下降至92岁时的9.845（7.443～13.023）。时期效应同样呈下降趋势，RR值由1992年的1.283（1.196～1.377）降至2022年的0.718（0.669～0.771），降幅达44.03%。队列效应亦持续减弱，RR值从1895年队列的3.170（0.203～49.458）下降至1990年队列的0.540（0.405～0.720），总体降幅达82.97%。见图4、5。
3　讨论
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吸烟是导致宫颈癌发病和死亡的重要危险因素，其通过烟草烟雾中的有害物质影响宫颈细胞增殖与分化，增加癌变风险[18]。本研究显示，1990—2021年中国归因于吸烟的宫颈癌死亡和DALY率均呈显著下降趋势，AAPC分别为-2.177和-2.054，且整体水平低于同类SDI地区，处于世界较低水平，提示中国在控烟与宫颈癌防控方面取得了一定成效。
从地区差异来看，五类SDI地区中，低和中高SDI地区的死亡与DALY率降幅较大，而高SDI地区降幅较小。这可能与不同地区的烟草流行率、防控措施强度及医疗资源分布有关,高SDI地区可能因原有吸烟暴露率较低，下降空间有限[19]；而低SDI地区由于原本得吸烟暴露率高及医疗水平的提升，实现了负担的快速降低。中国作为中高SDI地区，其疾病负担水平较低，可能得益于近年来烟草控制政策的推进，如我国于2006年正式加入《烟草控制框架公约》[20]，还将控烟纳入《健康中国行动计划（2019—2020）》[21]，这些政策的推进和宫颈癌筛查覆盖率的提高，使得吸烟所致宫颈癌的疾病负担得到一定程度的改善。不过中低和低SDI地区的疾病负担虽然下降快，但数值高于其它地区，提示在这些国家仍需增加宫颈癌三级防控措施和医疗水平，从而降低由吸烟导致的宫颈癌死亡率和伤残损失生命年。
年龄分布上，70～74岁及95+岁年龄组的死亡降幅最大，DALY率在70～74岁降幅最显著，提示高龄人群的吸烟相关宫颈癌负担改善明显，这可能与老年人群对控烟宣传的接受度提高及临床治疗水平进步有关[2]。但需注意，30～59岁年龄段在部分SDI地区仍呈上升趋势，提示需针对中青年人群加强控烟干预和30岁或以上的女性筛查[22]。
APC模型分析进一步揭示了疾病负担的动态变化：死亡率和DALY率的全局变化均呈下降趋势，时期效应和队列效应显著降低，尤其是队列效应从1895年到1990年降幅达82.97%。这表明随着时代发展，控烟政策的长期实施（如烟草广告管制、吸烟危害宣传）有效减少了新一代人群的吸烟暴露，而队列间的生活方式改善（如女性吸烟率下降）也降低了累积风险[23]。
与SDI的关联显示，中国归因于吸烟的宫颈癌负担低于同类地区，可能与中国在SDI提升过程中同步推进控烟与癌症防治工作有关，包括开展全民健康教育、提高宫颈癌的筛查、疫苗接种等等[3]。但需注意，中SDI地区59岁后死亡仍呈增长趋势，提示中等发展水平地区需警惕高龄人群的防控短板，避免因医疗资源分配不均导致负担反弹。
本研究仍存在局限：一是，尽管GBD数据已通过比较风险评估框架等方法，在较大程度上剔除了除吸烟之外其他混杂因素（如HPV感染、行为习惯等）的影响，但其结果仍受输入数据质量和流行病学证据强度的限制，在结果解读中应保持审慎。二是，数据仅覆盖30～95岁以上人群，未纳入0～30的青幼年群体；此外，APC模型未考虑个体吸烟时长、筛查频率等因素，可能影响结果解读。未来需结合个体队列数据，进一步验证吸烟与宫颈癌负担的剂量反应关系。
综上，中国归因于吸烟的宫颈癌负担下降趋势显著，这与控烟政策、筛查普及及公众健康意识的代际提升提升密切相关。未来应持续加强控烟教育，扩大高龄人群筛查覆盖，并针对不同SDI地区制定差异化防控策略，以巩固下降趋势。
基金
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  • 吴阶平医学基金(2022-18-46)
  • 陕西省科技厅重点研发计划一般项目-社会发展领域项目(2025SF-YBXM-518)
  • 陕西省科技厅计划项目(2020SF-052)
  • 秦创原中医药产业创新聚集区项目(L2024-QCY-ZYYJJQ-X175)
文献
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2026年第53卷第1期
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doi: 10.20043/j.cnki.MPM.202508408
  • 接收时间：2025-08-26
  • 首发时间：2026-11-02
  • 出版时间：2026-01-10
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  • 收稿日期：2025-08-26
基金
吴阶平医学基金(2022-18-46)
陕西省科技厅重点研发计划一般项目-社会发展领域项目(2025SF-YBXM-518)
陕西省科技厅计划项目(2020SF-052)
秦创原中医药产业创新聚集区项目(L2024-QCY-ZYYJJQ-X175)
作者信息
    1.新疆医科大学公共卫生学院，新疆 乌鲁木齐 830011
    2.乌鲁木齐市第一人民医院公共卫生科，新疆 乌鲁木齐 830002
    3.陕西中医药大学第一临床医学院

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李树林，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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