Article(id=1241025210019804041, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241025201983508979, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202410080, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1728316800000, receivedDateStr=2024-10-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773813067201, onlineDateStr=2026-03-18, pubDate=1744214400000, pubDateStr=2025-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773813067201, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773813067201, creator=13701087609, updateTime=1773813067201, updator=13701087609, issue=Issue{id=1241025201983508979, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='7', pageStart='1153', pageEnd='1344', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773813065285, creator=13701087609, updateTime=1773815493878, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241035388320543403, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241025201983508979, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241035388320543404, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241025201983508979, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1175, endPage=1181, ext={EN=ArticleExt(id=1241025210397291432, articleId=1241025210019804041, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Estimation of adult tobacco prevalence levels in each sub-district and township of Dingzhou city, Hebei Province in 2023 based on the small area estimation model, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

To understand the current situation of adult tobacco prevalence in each sub-district and township of Dingzhou city, Hebei Province, provide data support for formulating grass-roots tobacco control policies, and provide a reference for estimating tobacco prevalence indicators at the county-district level.

Methods

A multi-stage stratified cluster sampling method and Probability Proportional to Size (PPS) sampling method were used to conduct a questionnaire survey among permanent residents aged 15 and above in Dingzhou city. The survey data were cleaned, weighted, and analyzed using SAS 9.4. The current smoking rate, quitting rate, and second-hand smoke exposure rate in Dingzhou city were reported. The Small Area Estimation (SAE) method was used to estimate the above-mentioned indicators for each sub-district and township.

Results

A total of 7 660 valid questionnaires were collected in this survey, with an overall response rate of 68.70%. In 2023, the current smoking rate among people aged 15 and above in Dingzhou city was 22.27%, the quitting rate was 9.60%, and the second-hand smoke exposure rate among non-smokers was 36.84%. The estimation results of the SAE model showed that there were differences in tobacco prevalence monitoring indicators among different sub-districts and townships. Townships such as Xingyi Town, Liqinggu Town, and Dongliuchun Township in the southern part of Dingzhou city had relatively high current smoking rates (25%-35%). Some townships in the northwest and southeast regions had relatively low quitting rates (less than 10%), while the sub-districts and townships with relatively high second-hand smoke exposure rates were more scattered, with the rates in Dongting Town and Xizhong Town exceeding 50%.

Conclusion

The SAE model can be used to estimate tobacco prevalence monitoring indicators at the county-district and even sub-district and township levels. Currently, the tobacco prevalence situation in some sub-districts and townships of Dingzhou city is relatively severe. Targeted grass-roots tobacco control work should be carried out, the construction of smoke-free environments should be strengthened, and grass-roots smoking cessation services should be promoted.

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目的

了解河北省定州市各街道乡镇成人烟草流行现状,为制定基层控烟政策提供数据支持,同时为县区层面烟草流行指标估算提供参考依据。

方法

采用多阶段分层整群抽样法和容量比例概率抽样(probability proportional to size,PPS)方法,对定州市15岁及以上常住居民进行问卷调查。调查数据使用SAS 9.4进行清洗、加权和分析。报告定州市现在吸烟率、戒烟率和二手烟暴露率,使用小区域估计(small area estimation,SAE)方法对各街道乡镇的上述指标进行估算。

结果

本次调查有效问卷共7 660份,整体应答率为68.70%。2023年定州市15岁及以上人群的现在吸烟率为22.27%,戒烟率为9.60%,非吸烟人群的二手烟暴露率为36.84%。SAE模型估算结果显示,不同街道乡镇之间的烟草流行监测指标存在差异。位于定州市南部的刑邑镇、李亲顾镇、东留春乡等乡镇现在吸烟率较高(25%~35%),西北、东南地区部分乡镇戒烟率较低(低于10%),而二手烟暴露率较高的街道乡镇较分散,其中东亭镇、息冢镇超过50%。

结论

SAE模型可用于估算县区乃至乡镇街道层面的烟草流行监测指标。目前定州市部分街道乡镇的烟草流行形势较严峻,应有针对性地开展基层控烟工作,加强无烟环境建设,推广基层戒烟服务。

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万霞,E-mail:
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李晓玥(1999—),女,硕士在读,研究方向:疾病负担和烟草控制相关研究

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Study on influencing factors of comprehensive smoke-free policy in Chinese provincial capitals and cities above[J].Chinese Journal of Health Education202238(11): 973-977.(In Chinese), articleTitle=Study on influencing factors of comprehensive smoke-free policy in Chinese provincial capitals and cities above, refAbstract=null)], funds=[Fund(id=1241025220694307345, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, awardId=2060204, language=CN, fundingSource=全国重点实验室专项经费(2060204), fundOrder=null, country=null), Fund(id=1241025220786582039, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, awardId=null, language=CN, fundingSource=北京协和医学院2023年暑期社会实践经费, fundOrder=null, country=null), Fund(id=1241025220862079516, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, awardId=2023-I2M-2-001, language=CN, fundingSource=医科院创新工程(2023-I2M-2-001), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241025212381196417, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, xref=1., ext=[AuthorCompanyExt(id=1241025212402167941, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, companyId=1241025212381196417, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=National Key Laboratory of Respiratory and Comorbid Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing 100005, China), AuthorCompanyExt(id=1241025212444110986, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, companyId=1241025212381196417, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中国医学科学院基础医学研究所 北京协和医学院基础学院,呼吸和共病全国重点实验室,北京 100005)]), AuthorCompany(id=1241025212515414162, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, xref=2., ext=[AuthorCompanyExt(id=1241025212519608467, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, companyId=1241025212515414162, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.定州市疾病预防控制中心(定州市卫生监督所))])], figs=[ArticleFig(id=1241025219641536995, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, language=EN, label=Figure 1, caption=Comparison before and after SAE model correction for tobacco epidemic indicators by different genders of each township in Dingzhou city in 2023, figureFileSmall=t2HAd/aDudEef5/8X11a0g==, figureFileBig=qaAWLZPPO57rfVW7osH2FA==, tableContent=null), ArticleFig(id=1241025219750588909, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, language=CN, label=图1, caption=2023年定州市各街道乡镇不同性别人群烟草流行指标的SAE模型校正前后比较

注:图A现在吸烟率(合计);图B现在吸烟率(男性);图C现在吸烟率(女性);图D戒烟率(合计);图E戒烟率(男性);图F戒烟率(女性);图G二手烟暴露率(合计);图H二手烟暴露率(男性);图I二手烟暴露率(女性)。

, figureFileSmall=t2HAd/aDudEef5/8X11a0g==, figureFileBig=qaAWLZPPO57rfVW7osH2FA==, tableContent=null), ArticleFig(id=1241025220010635765, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, language=EN, label=Figure 2, caption=Results after SAE model correction for tobacco epidemic indicators by different genders of each township in Dingzhou city in 2023, figureFileSmall=QaNkPHBI9oF4FRGvRnzOPw==, figureFileBig=evoxX/2dbTXJn3Rr+Zdl7w==, tableContent=null), ArticleFig(id=1241025220174213627, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, language=CN, label=图2, caption=2023年定州市各街道乡镇不同性别人群烟草流行指标的SAE模型校正后结果

注:图A现在吸烟率(合计);图B现在吸烟率(男性);图C现在吸烟率(女性);图D戒烟率(合计);图E戒烟率(男性);图F戒烟率(女性);图G二手烟暴露率(合计);图H二手烟暴露率(男性);图I二手烟暴露率(女性);图本图基于审图号为GS京(2022)1061号标准地图制作,底图无修改。

, figureFileSmall=QaNkPHBI9oF4FRGvRnzOPw==, figureFileBig=evoxX/2dbTXJn3Rr+Zdl7w==, tableContent=null), ArticleFig(id=1241025220291654143, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, language=EN, label=Table 1, caption=

Demographic characteristics of tobacco epidemic survey among people aged 15 years and above in Dingzhou city in 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
人口学特征加权后未加权
样本量
百分率(%,95%CI样本量
总体100883 6377 660
性别
男性48.95(48.85~49.05)432 5463 656
女性51.05(50.95~51.15)451 0914 004
年龄(岁)
15~2411.56(11.50~11.63)102 177514
25~4434.96(34.86~35.06)308 9371 752
45~6435.72(35.62~35.82)315 6783 262
≥6517.75(17.67~17.83)156 8452 132
居住地
城市50.14(50.03~50.24)443 0463 327
农村49.86(49.76~49.97)440 5914 333
教育水平
小学及以下25.04(24.94~25.13)221 2202 647
初中毕业43.00(42.90~43.10)379 9563 353
高中毕业17.92(17.84~18.00)158 351988
大专及以上13.05(12.98~13.12)115 336589
其他0.99(0.97~1.01)8 77483
职业
农民50.89(50.79~51.00)449 7114 647
政府/事业单位人员1.25(1.23~1.28)11 07461
企业、商业、服务业人员11.18(11.12~11.25)98 804550
教师1.36(1.34~1.39)12 04454
医务工作者0.91(0.90~0.93)8 08446
在校学生7.34(7.29~7.40)64 883309
无业6.80(6.75~6.85)60 070554
离退休人员2.32(2.29~2.35)20 505186
其他17.93(17.85~18.01)158 4621 253
), ArticleFig(id=1241025220400706052, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, language=CN, label=表1, caption=

2023年定州市15岁及以上人群烟草流行调查人口学特征分布

, figureFileSmall=null, figureFileBig=null, tableContent=
人口学特征加权后未加权
样本量
百分率(%,95%CI样本量
总体100883 6377 660
性别
男性48.95(48.85~49.05)432 5463 656
女性51.05(50.95~51.15)451 0914 004
年龄(岁)
15~2411.56(11.50~11.63)102 177514
25~4434.96(34.86~35.06)308 9371 752
45~6435.72(35.62~35.82)315 6783 262
≥6517.75(17.67~17.83)156 8452 132
居住地
城市50.14(50.03~50.24)443 0463 327
农村49.86(49.76~49.97)440 5914 333
教育水平
小学及以下25.04(24.94~25.13)221 2202 647
初中毕业43.00(42.90~43.10)379 9563 353
高中毕业17.92(17.84~18.00)158 351988
大专及以上13.05(12.98~13.12)115 336589
其他0.99(0.97~1.01)8 77483
职业
农民50.89(50.79~51.00)449 7114 647
政府/事业单位人员1.25(1.23~1.28)11 07461
企业、商业、服务业人员11.18(11.12~11.25)98 804550
教师1.36(1.34~1.39)12 04454
医务工作者0.91(0.90~0.93)8 08446
在校学生7.34(7.29~7.40)64 883309
无业6.80(6.75~6.85)60 070554
离退休人员2.32(2.29~2.35)20 505186
其他17.93(17.85~18.01)158 4621 253
), ArticleFig(id=1241025220518146568, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, language=EN, label=Table 2, caption=

Weighted rate of tobacco epidemic indicators among people aged 15 years and above in Dingzhou city in 2023[%(95%CI)]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目现在吸烟率戒烟率二手烟暴露率
总体22.27(22.18~22.36)9.60(9.48~9.72)36.84(36.73~36.95)
性别
男性44.26(44.12~44.41)9.50(9.38~9.63)37.74(37.55~37.94)
女性1.18(1.15~1.21)13.08(12.24~13.93)36.35(36.21~36.49)
年龄(岁)
15~248.24(8.07~8.40)5.35(4.88~5.82)31.12(30.82~31.42)
25~4425.64(25.48~25.79)3.22(3.10~3.34)41.59(41.39~41.80)
45~6424.25(24.10~24.40)11.55(11.34~11.76)38.34(38.14~38.53)
≥6520.79(20.59~20.99)19.29(18.90~19.67)29.49(29.23~29.74)
居住地
城市22.74(22.61~22.86)7.02(6.87~7.17)39.72(39.56~39.88)
农村21.80(21.68~21.92)12.16(11.96~12.35)33.98(33.82~34.14)
教育水平
小学及以下20.33(20.16~20.50)14.67(14.37~14.98)35.19(34.97~35.41)
初中毕业25.19(25.05~25.32)8.78(8.61~8.95)38.52(38.34~38.70)
高中毕业26.23(26.02~26.45)8.11(7.86~8.36)33.97(33.70~34.24)
大专及以上11.87(11.69~12.06)1.63(1.42~1.84)38.76(38.46~39.06)
职业
农民24.73(24.60~24.86)11.16(10.99~11.34)36.30(36.14~36.46)
政府/事业单位人员39.02(38.11~39.93)6.37(5.67~7.08)65.37(64.23~66.50)
企业/商业/服务业人员25.33(25.06~25.60)3.93(3.70~4.17)41.74(41.38~42.09)
教师9.78(9.25~10.31)41.25(40.32~42.17)
医务工作者6.12(5.60~6.64)8.08(5.78~10.38)54.63(53.51~55.75)
在校学生2.92(2.79~3.05)29.34(28.98~29.69)
无业10.95(10.70~11.20)15.06(14.27~15.86)36.26(35.86~36.67)
离退休人员16.06(15.56~16.56)14.80(13.68~15.92)24.37(23.73~25.01)
其他27.03(26.81~27.25)8.21(7.96~8.45)38.24(37.96~38.52)
), ArticleFig(id=1241025220602032653, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241025210019804041, language=CN, label=表2, caption=

2023年定州市15岁及以上人群烟草流行指标加权后率值[%(95%CI)]

, figureFileSmall=null, figureFileBig=null, tableContent=
项目现在吸烟率戒烟率二手烟暴露率
总体22.27(22.18~22.36)9.60(9.48~9.72)36.84(36.73~36.95)
性别
男性44.26(44.12~44.41)9.50(9.38~9.63)37.74(37.55~37.94)
女性1.18(1.15~1.21)13.08(12.24~13.93)36.35(36.21~36.49)
年龄(岁)
15~248.24(8.07~8.40)5.35(4.88~5.82)31.12(30.82~31.42)
25~4425.64(25.48~25.79)3.22(3.10~3.34)41.59(41.39~41.80)
45~6424.25(24.10~24.40)11.55(11.34~11.76)38.34(38.14~38.53)
≥6520.79(20.59~20.99)19.29(18.90~19.67)29.49(29.23~29.74)
居住地
城市22.74(22.61~22.86)7.02(6.87~7.17)39.72(39.56~39.88)
农村21.80(21.68~21.92)12.16(11.96~12.35)33.98(33.82~34.14)
教育水平
小学及以下20.33(20.16~20.50)14.67(14.37~14.98)35.19(34.97~35.41)
初中毕业25.19(25.05~25.32)8.78(8.61~8.95)38.52(38.34~38.70)
高中毕业26.23(26.02~26.45)8.11(7.86~8.36)33.97(33.70~34.24)
大专及以上11.87(11.69~12.06)1.63(1.42~1.84)38.76(38.46~39.06)
职业
农民24.73(24.60~24.86)11.16(10.99~11.34)36.30(36.14~36.46)
政府/事业单位人员39.02(38.11~39.93)6.37(5.67~7.08)65.37(64.23~66.50)
企业/商业/服务业人员25.33(25.06~25.60)3.93(3.70~4.17)41.74(41.38~42.09)
教师9.78(9.25~10.31)41.25(40.32~42.17)
医务工作者6.12(5.60~6.64)8.08(5.78~10.38)54.63(53.51~55.75)
在校学生2.92(2.79~3.05)29.34(28.98~29.69)
无业10.95(10.70~11.20)15.06(14.27~15.86)36.26(35.86~36.67)
离退休人员16.06(15.56~16.56)14.80(13.68~15.92)24.37(23.73~25.01)
其他27.03(26.81~27.25)8.21(7.96~8.45)38.24(37.96~38.52)
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基于小区域估计模型估算2023年河北省定州市各街道乡镇成人烟草流行水平
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李晓玥 1 , 么常强 2 , 李丹颖 1 , 任丽娜 2 , 郭晓璟 1 , 冯梦露 2 , 蔡泽敏 1 , 张丽 2 , 张猛 2 , 万霞 1
现代预防医学 | 流行病与统计方法 2025,52(7): 1175-1181
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现代预防医学 | 流行病与统计方法 2025, 52(7): 1175-1181
基于小区域估计模型估算2023年河北省定州市各街道乡镇成人烟草流行水平
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李晓玥1, 么常强2, 李丹颖1, 任丽娜2, 郭晓璟1, 冯梦露2, 蔡泽敏1, 张丽2, 张猛2, 万霞1
作者信息
  • 1.中国医学科学院基础医学研究所 北京协和医学院基础学院,呼吸和共病全国重点实验室,北京 100005
  • 2.定州市疾病预防控制中心(定州市卫生监督所)
  • 李晓玥(1999—),女,硕士在读,研究方向:疾病负担和烟草控制相关研究

通讯作者:

万霞,E-mail:
Estimation of adult tobacco prevalence levels in each sub-district and township of Dingzhou city, Hebei Province in 2023 based on the small area estimation model
Xiao-yue LI1, Chang-qiang YAO2, Dan-ying LI1, Li-na REN2, Xiao-jing GUO1, Meng-lu FENG2, Ze-min CAI1, Li ZHANG2, Meng ZHANG2, Xia WAN1
Affiliations
  • National Key Laboratory of Respiratory and Comorbid Diseases, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing 100005, China
出版时间: 2025-04-10 doi: 10.20043/j.cnki.MPM.202410080
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目的

了解河北省定州市各街道乡镇成人烟草流行现状,为制定基层控烟政策提供数据支持,同时为县区层面烟草流行指标估算提供参考依据。

方法

采用多阶段分层整群抽样法和容量比例概率抽样(probability proportional to size,PPS)方法,对定州市15岁及以上常住居民进行问卷调查。调查数据使用SAS 9.4进行清洗、加权和分析。报告定州市现在吸烟率、戒烟率和二手烟暴露率,使用小区域估计(small area estimation,SAE)方法对各街道乡镇的上述指标进行估算。

结果

本次调查有效问卷共7 660份,整体应答率为68.70%。2023年定州市15岁及以上人群的现在吸烟率为22.27%,戒烟率为9.60%,非吸烟人群的二手烟暴露率为36.84%。SAE模型估算结果显示,不同街道乡镇之间的烟草流行监测指标存在差异。位于定州市南部的刑邑镇、李亲顾镇、东留春乡等乡镇现在吸烟率较高(25%~35%),西北、东南地区部分乡镇戒烟率较低(低于10%),而二手烟暴露率较高的街道乡镇较分散,其中东亭镇、息冢镇超过50%。

结论

SAE模型可用于估算县区乃至乡镇街道层面的烟草流行监测指标。目前定州市部分街道乡镇的烟草流行形势较严峻,应有针对性地开展基层控烟工作,加强无烟环境建设,推广基层戒烟服务。

烟草流行  /  吸烟  /  小区域估计  /  控烟
Objective

To understand the current situation of adult tobacco prevalence in each sub-district and township of Dingzhou city, Hebei Province, provide data support for formulating grass-roots tobacco control policies, and provide a reference for estimating tobacco prevalence indicators at the county-district level.

Methods

A multi-stage stratified cluster sampling method and Probability Proportional to Size (PPS) sampling method were used to conduct a questionnaire survey among permanent residents aged 15 and above in Dingzhou city. The survey data were cleaned, weighted, and analyzed using SAS 9.4. The current smoking rate, quitting rate, and second-hand smoke exposure rate in Dingzhou city were reported. The Small Area Estimation (SAE) method was used to estimate the above-mentioned indicators for each sub-district and township.

Results

A total of 7 660 valid questionnaires were collected in this survey, with an overall response rate of 68.70%. In 2023, the current smoking rate among people aged 15 and above in Dingzhou city was 22.27%, the quitting rate was 9.60%, and the second-hand smoke exposure rate among non-smokers was 36.84%. The estimation results of the SAE model showed that there were differences in tobacco prevalence monitoring indicators among different sub-districts and townships. Townships such as Xingyi Town, Liqinggu Town, and Dongliuchun Township in the southern part of Dingzhou city had relatively high current smoking rates (25%-35%). Some townships in the northwest and southeast regions had relatively low quitting rates (less than 10%), while the sub-districts and townships with relatively high second-hand smoke exposure rates were more scattered, with the rates in Dongting Town and Xizhong Town exceeding 50%.

Conclusion

The SAE model can be used to estimate tobacco prevalence monitoring indicators at the county-district and even sub-district and township levels. Currently, the tobacco prevalence situation in some sub-districts and townships of Dingzhou city is relatively severe. Targeted grass-roots tobacco control work should be carried out, the construction of smoke-free environments should be strengthened, and grass-roots smoking cessation services should be promoted.

Tobacco prevalence  /  Smoking  /  Small area estimation  /  Tobacco control
李晓玥, 么常强, 李丹颖, 任丽娜, 郭晓璟, 冯梦露, 蔡泽敏, 张丽, 张猛, 万霞. 基于小区域估计模型估算2023年河北省定州市各街道乡镇成人烟草流行水平. 现代预防医学, 2025 , 52 (7) : 1175 -1181 . DOI: 10.20043/j.cnki.MPM.202410080
Xiao-yue LI, Chang-qiang YAO, Dan-ying LI, Li-na REN, Xiao-jing GUO, Meng-lu FENG, Ze-min CAI, Li ZHANG, Meng ZHANG, Xia WAN. Estimation of adult tobacco prevalence levels in each sub-district and township of Dingzhou city, Hebei Province in 2023 based on the small area estimation model[J]. Modern Preventive Medicine, 2025 , 52 (7) : 1175 -1181 . DOI: 10.20043/j.cnki.MPM.202410080
我国是全球最大的烟草消费和生产国,2020年我国15岁以上人群吸烟率高达25.8%[1],这与广大烟民戒烟意愿较低和烟草危害认知不足有关。定州市为河北省直管市,下辖25个街道和乡镇,常住人口110万,是华北五省市人口最多的县(市)[2]。定州是中国公共卫生事业的发源地之一[3],以晏阳初先生为首的平民教育促进会曾在定县进行农村卫生实验[4],陈志潜先生亦在此创立了著名的“农村三级保健网”[5-6]。为了解农村公共卫生教育对当地居民健康意识的影响是否会导致其烟草流行水平不同于全国,以及不同乡镇街道烟草流行情况是否一致,本研究在定州市开展烟草流行病学调查,以填补当地数据空白,为制订精准控烟干预政策提供依据,满足政府科学决策和精细化管理的需求[7]。同时为减小估计偏差,本研究使用小区域估计(small area estimation, SAE)方法[8-10],基于地理空间分布原理,结合其他协变量建立混合效应模型,对定州市各街道乡镇的烟草监测指标进行估算。
本研究团队于2023年8月对定州市15岁及以上常住居民进行烟草流行调查。样本量计算按性别、城乡、地理位置分为6层,每层样本量计算公式为。其中N为样本量,μ=1.96,吸烟率p取2018年中国成人吸烟率26.6%[11],设计效率deff=2,相关误差r取15%,δ=γ×p。计算最小样本量为7 544。参考全球成人烟草调查(Global Adult Tobacco Survey,GATS)中国项目[12]以及当地情况,设家庭合格率为90%,家庭应答率为95%,家庭筛查率为95%,个人合格率为98%,个人应答率为85%,计算最小抽样户数为11 151户。采用多阶段分层整群抽样设计,按容量比例概率抽样法(probability proportional to size,PPS)进行抽样。对抽中家庭进行入户调查,并采用KISH表抽取1名≥15岁的成员开展问卷调查。
本次调查获得受访者本人或监护人知情同意,受访者个人信息已脱敏处理,本研究已通过中国医学科学院基础医学研究所伦理委员会审核通过(ZS2023021)。
使用抽样权重、无应答调整系数和事后分层调整系数进行数据加权,最终权重为三者乘积[13]。抽样权重为各阶段抽样概率倒数之积。以居委会(村)为单位校正无应答偏倚,无应答调整系数为加权后样本应答率的倒数。按性别和5岁年龄组分层,事后分层调整系数为各层内定州市第七次人口普查人数除以加权样本数。
将加权后数据作为建模数据集,以性别、年龄、城乡、教育程度、职业、民族等为协变量构建logistic回归混合效应模型,模型系数估计采用最大似然法。对模型和各协变量系数进行显著性检验,剔除不显著变量,直至均有统计学意义(P<0.05),最终模型为:
其中Ps,g,a为[s街道(乡镇)、g性别、a年龄组]模型校正后指标率值,gender为性别,age为年龄组,rural为城乡,education为教育程度,race为民族,β0为固定截距,β1~β5为固定斜率,μs为随机截距。
计算模型不加随机截距时的残差值(取对数),对残差进行局部加权回归,权重包括年龄组权重(Wa)和空间权重(WS),公式如下:
Wa为年龄组权重,a为监测点年龄组,a0为对照点年龄组,ω为年龄权重调整系数,参照GBD设置为2[14]
WS=s0为指定街道乡镇的最终权重,WS≠s0为非指定街道乡镇的最终权重,ζ为空间平滑系数,参考Wang等[15]设置为0.6。
对各街道乡镇不同年龄组,以残差回归估计值代替原模型中的μs,构建最终的SAE模型。
使用SAS 9.4进行数据清洗、加权和分析,报告的所有率均为加权后率。现在吸烟率、戒烟率、二手烟暴露率定义参考《2018年中国成人烟草调查报告》[11]
本次调查实际抽取11 348户,完成有效问卷7 660份,家庭应答率为70.40%,个人应答率为97.59%,整体应答率为68.70%。表1为加权样本的人口统计特点,男女比例分别为48.07%和51.93%,城乡居民比例分别为50.14%和49.86%。样本人群在45~64岁的最多,为35.72%,其次为25~44岁,为34.96%。教育水平以初中居多,为43.00%,职业以务农为主,占50.89%。
2023年定州市15岁及以上人群的现在吸烟率为22.27%,戒烟率为9.60%,非吸烟者的二手烟暴露率为38.64%,见表2;不同性别、年龄组、居住地、文化程度和职业的人群中,三项指标均存在差异。其中,男性吸烟率、戒烟率、非吸烟者的二手烟暴露率分别为44.26%、9.50%、37.74%,女性分别为1.18%、13.08%、36.35%。年龄在25~44岁的人群现在吸烟率和二手烟暴露率较高,分别为25.64%和41.59%,戒烟率(3.22%)低于其他年龄段人群。不同职业人群中,政府和事业单位工作人员现在吸烟率和二手烟暴露率较为突出,分别达到39.02%和65.37%。
总体上看,合计及男性现在吸烟率、二手烟暴露率几个指标经SAE校正前后变化不大,而女性吸烟率和女性戒烟率在校正前后变化较大,主要集中在南部(东亭镇、东留春乡、高蓬镇和刑邑镇)和北部(清风店镇、留早镇、李亲顾镇)几个乡镇,其中东亭镇、李亲顾镇等有多个监测指标在校正前后有较大差距。见图1
图2展示了各街道乡镇不同性别人群上述指标的SAE模型估算结果。男性现在吸烟率南部高于北部,其中刑邑镇、东留春乡、明月店镇、南城区街道和砖路镇超过54%;女性吸烟率分布与男性类似,其中刑邑镇最高,超过2%。戒烟率与现在吸烟率的高低分布不一致,杨家庄乡、东亭镇男性戒烟率最高(超过30%),位于西北和东南地区的部分乡镇男性戒烟率较低,包括大辛庄镇、李亲顾镇在内的共计12个街道和乡镇戒烟率低于10%。女性戒烟率总体高于男性,其中刑邑镇最高(大于30%),号头庄回族乡、西城区街道、长安路街道和明月店镇较低(低于10%)。二手烟暴露率高的镇街分布较分散,其中以东亭镇和息冢镇最为严重,总体二手烟暴露率超过50%;暴露率较低的乡镇是留早镇和大辛庄镇,总体二手烟暴露率低于20%。男性和女性的二手烟暴露情况分布较为一致。
本次调查结果显示,定州市15岁及以上人群现在吸烟率为22.27%,低于2020年全国(25.8%)[1]及河北省(24.86%)[16]现在吸烟率;非吸烟者二手烟暴露率为38.64%,低于2018年全国水平的68.1%[11]。由于定州市近几十年来并无专门的控烟项目投入,因此其烟草流行水平可能与早年开展的农村公共卫生教育以及当地人群健康意识较高有关。然而定州市15岁及以上吸烟人群戒烟成功率仅9.60%,低于2018年全国水平(20.1%)[11],亟需加强控烟宣传,推广基层戒烟门诊、简短戒烟建议等戒烟服务。总体来看,定州市距实现《“健康中国2030”规划纲要》的控烟目标(15岁以上人群吸烟率下降至20%)[17]仍有较大差距。本次调查人群中,男性、25~44岁的青中年群体以及政府和事业单位工作人员的吸烟问题较为突出。这提示未来控烟工作应将上述群体作为戒烟干预的重点人群,同时继续开展无烟单位创建工作,倡导公职人员戒烟。
定州市现在吸烟率总体南部高于北部,部分乡镇超过54%,提示当地政府需要重点关注以上乡镇的烟草流行情况,做好控烟干预工作。在上述地区特别是李亲顾镇、明月店镇、南城区街道和东留春乡,在吸烟率高的同时戒烟率低于10%,提示吸烟者的戒烟意愿和戒烟行动不足。此外,二手烟暴露率较高的街道乡镇分布较分散,表明二手烟暴露的现象较为普遍。针对以上结果,未来定州市应根据2008年WHO提出的扭转烟草流行的“MPOWER”策略,加强向戒烟者提供戒烟帮助(“O”策略)和加强无烟环境建设(“P”策略)两大策略[18]
本研究发现,总体及男性吸烟率、二手烟暴露率指标在SAE校正前后较稳定,而女性吸烟率和戒烟率变化较大。这表明在评估县区层面的烟草流行情况时,使用SAE模型对于估算上述不稳定的指标有重要意义。由于女性吸烟率较低,抽样时难以抽取到女性吸烟者,抽样误差会导致直接估计时某些乡镇的指标偏高或偏低,甚至出现女性现在吸烟率和戒烟率为0或100%的结果,这显然无法代表当地实际情况。因此需要找到一种间接估计方法,以增加“有效”样本大小,减少估计偏差。目前SAE方法在农业统计、社会统计等领域应用较广泛,但国内少见烟草流行的SAE研究[19]。本研究通过结合人口学特征、地理空间分布等协变量建立SAE模型,对异常点进行平滑,从而获得相对准确的估算结果,也将为国内烟草流行研究提供思路。
目前我国尚无全国性公共场所禁烟政策[20],考虑现实意义和经济社会平稳运行的需要,短期内大范围的无烟立法难以实现,省、市级政府在制定控烟政策时往往面临巨大压力。在此情况下,应首先在烟草流行形势严峻的小区域内加强控烟,由点及面推进烟草防控。定州市在上世纪前叶创立的“定县模式”为中国近代公共卫生事业的起步和发展作出了不可磨灭的贡献[35],本研究首次提供了具有定州市代表性的烟草流行数据,为控烟策略的制定提供了数据支持,将进一步推动定州市相关部门加大控烟力度,建设无烟环境和推广基层戒烟服务。
  • 全国重点实验室专项经费(2060204)
  • 北京协和医学院2023年暑期社会实践经费
  • 医科院创新工程(2023-I2M-2-001)
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2025年第52卷第7期
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doi: 10.20043/j.cnki.MPM.202410080
  • 接收时间:2024-10-08
  • 首发时间:2026-03-18
  • 出版时间:2025-04-10
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  • 收稿日期:2024-10-08
基金
全国重点实验室专项经费(2060204)
北京协和医学院2023年暑期社会实践经费
医科院创新工程(2023-I2M-2-001)
作者信息
    1.中国医学科学院基础医学研究所 北京协和医学院基础学院,呼吸和共病全国重点实验室,北京 100005
    2.定州市疾病预防控制中心(定州市卫生监督所)

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Percentage of total
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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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