Article(id=1324078102531416322, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077868950631142, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202510063, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1760025600000, receivedDateStr=2025-10-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614419825, onlineDateStr=2026-11-02, pubDate=1771948800000, pubDateStr=2026-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614419825, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614419825, creator=13701087609, updateTime=1793614419825, updator=13701087609, issue=Issue{id=1324077868950631142, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='4', pageStart='577', pageEnd='768', issueExtLink='null', onlineDate='null', pubDate='1771948800000', pubDateStr='2026-02-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614364134, creator='13701087609', updateTime=1793614446224, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078213328142371, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077868950631142, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078213332336676, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324077868950631142, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=741, endPage=746, ext={EN=ArticleExt(id=1324078102946652419, articleId=1324078102531416322, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Analysis of the prevalence ofdiabetes mellitus and its influencing factors among adult residents, Guangxi, 2023, columnId=1228016573156360233, journalTitle=Modern Preventive Medicine, columnName=Disease Control and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the prevalence and its influencing factors among adult residents in Guangxi in 2023, so as to provide scientific basis for accurate prevention and control of diabetes mellitus in Guangxi.

Methods

A multi-stage stratified cluster random sampling method was used to select residents aged 18 years and older in Guangxi. Participants completed questionnaires, physical examinations, and laboratory tests. Data were analyzed using R 4.5.1 software, including χ2 tests and multivariable logistic regression.

Results

Among the 6 187 subjects, 1 117 were identified as diabetic patients, with a standardized prevalence of diabetes 13.8 %. Multivariate analysis revealed that age (compared with 18-44 years old, 45-59 years old: OR=2.249, 95 % CI: 1.290-3.919; age 60 and above: OR = 3.428, 95 % CI: 1.894-6.205), retirees (compared with agricultural, forestry, animal husbandry, fishery and water conservancy production personnel, OR=1.847, 95 % CI: 1.151-2.962), overweight and obesity (compared with normal weight, overweight: OR=2.067, 95 % CI: 1.496-2.856; obesity: OR=2.326, 95 % CI: 1.506-3.595), and hypertension (compared with non-hypertensive individuals, OR=2.110, 95 % CI: 1.546-2.880) were significant risk factors for diabetes.

Conclusion

In 2023, the prevalence of diabetes in Guangxi showed a rapid rising trend. It is necessary to implement targeted prevention and control for key populations such as middle-aged and elderly people, overweight or obese people and individuals with hypertension.

, authors=Jin-mei HUANG1, Xiao-yun JIANG1, Mei-yan TANG3, You-ming TENG1, Yan-xu ZHONG1, 2, Wei MAO1, authorsList=Jin-mei HUANG, Xiao-yun JIANG, Mei-yan TANG, You-ming TENG, Yan-xu ZHONG, Wei MAO, authorCompany=null, correspAuthors=Yan-xu ZHONG, Wei MAO, 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=1324078105874276614, articleId=1324078102531416322, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=广西2023年成年居民糖尿病流行现状及其影响因素分析, columnId=1228016573844226129, journalTitle=现代预防医学, columnName=疾病预防控制, runingTitle=null, highlight=null, articleAbstract=
目的

分析广西2023年成年居民糖尿病患病情况及其影响因素,为广西糖尿病精准防控提供科学依据。

方法

采用多阶段分层整群随机抽样,对广西18岁及以上居民进行问卷调查、身体测量和实验室检测,使用R 4.5.1软件进行χ2检验和logistic回归分析。

结果

在6 187人调查对象中,共有1 117人确定为糖尿病患者,糖尿病标化患病率为13.8%。多因素分析结果显示,年龄增长(与18~44岁相比,45~59岁:OR=2.249,95%CI : 1.290~3.919;60岁及以上:OR=3.428,95%CI : 1.894~6.205、退休人员(与农林牧渔水利业生产人员相比,OR=1.847,95%CI : 1.151~2.962),超重和肥胖(与正常体重相比,超重:OR=2.067,95%CI : 1.496~2.856;肥胖:OR=2.326,95%CI : 1.506~3.595)以及患有高血压(与未患高血压相比,OR=2.110,95%CI : 1.546~2.880)是糖尿病的危险因素。

结论

广西糖尿病患病率呈现快速上升趋势,需针对中老年人、超重或肥胖以及患有高血压等重点人群,实施精准防控。

, authors=黄金梅1, 蒋小云1, 唐美艳3, 滕有明1, 钟延旭1, 2, 毛玮1, authorsList=黄金梅, 蒋小云, 唐美艳, 滕有明, 钟延旭, 毛玮, authorCompany=null, correspAuthors=钟延旭, 毛玮, authorNote=

黄金梅和蒋小云为共同第一作者。

黄金梅(1984—),女,硕士,副主任医师,研究方向:慢性病防控

蒋小云(1996—),女,硕士,研究方向:慢性病防控

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毛玮和钟延旭为共同通信作者。
毛玮,E-mail:
钟延旭,E-mail:
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Cell Metabolism, 2022, 34(1): 11-20., articleTitle=Why does obesity cause diabetes?, refAbstract=null), Reference(id=1324078115164660054, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, doi=null, pmid=null, pmcid=null, year=2021, volume=9, issue=6, pageStart=373, pageEnd=392, url=null, language=null, rfNumber=[20], rfOrder=27, authorNames=Pan XF, Wang LM, Pan A, journalName=The Lancet Diabetes & Endocrinology, refType=null, unstructuredReference=Pan XF, Wang LM, Pan A. Epidemiology and determinants of obesity in China[J]. The Lancet Diabetes & Endocrinology, 2021, 9(6): 373-392., articleTitle=Epidemiology and determinants of obesity in China, refAbstract=null), Reference(id=1324078115277906263, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, doi=null, pmid=null, pmcid=null, year=2025, volume=7, issue=1, pageStart=16, pageEnd=34, url=null, language=null, rfNumber=[21], rfOrder=28, authorNames=Jia WP, Chan JC, Wong TY, journalName=Nature Metabolism, refType=null, unstructuredReference=Jia WP, Chan JC, Wong TY, et al. Diabetes in China: epidemiology, pathophysiology and multi-omics[J]. Nature Metabolism, 2025, 7(1): 16-34., articleTitle=Diabetes in China: epidemiology, pathophysiology and multi-omics, refAbstract=null), Reference(id=1324078115361792344, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, doi=null, pmid=null, pmcid=null, year=2023, volume=39, issue=6, pageStart=720, pageEnd=724, url=null, language=null, rfNumber=[22], rfOrder=29, authorNames=罗雪纯, 姜莹莹, 吉宁, journalName=中国公共卫生, refType=null, unstructuredReference=罗雪纯,姜莹莹,吉宁,等.中国6省(直辖市)社区糖尿病患者共病患病情况及其影响因素分析[J].中国公共卫生,2023,39(6):720-724., articleTitle=中国6省(直辖市)社区糖尿病患者共病患病情况及其影响因素分析, refAbstract=null), Reference(id=1324078115496010073, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, doi=null, pmid=null, pmcid=null, year=2023, volume=39, issue=6, pageStart=720, pageEnd=724, url=null, language=null, rfNumber=[22], rfOrder=30, authorNames=Luo XC, Jiang YY, Ji N, journalName=Chinese Journal of Public Health, refType=null, unstructuredReference=Luo XC, Jiang YY, Ji N, et al. Prevalence and influencing factors of multimorbidity among community diabetic patients in six provincial-level administrative divisions of China[J]. Chinese Journal of Public Health, 2023, 39(6): 720-724. (In Chinese), articleTitle=Prevalence and influencing factors of multimorbidity among community diabetic patients in six provincial-level administrative divisions of China, refAbstract=null)], funds=[Fund(id=1324078110924218681, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, awardId=S2021066, language=CN, fundingSource=广西医疗卫生适宜技术开发与推广应用项目(S2021066), fundOrder=null, country=null), Fund(id=1324078111003910458, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, awardId=22253988, language=CN, fundingSource=广西壮族自治区疾病预防控制中心青年博士提升科研能力课题(22253988), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1324078106121740551, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, xref=1., ext=[AuthorCompanyExt(id=1324078106130129160, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, companyId=1324078106121740551, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Chronic Non-communicable Disease Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi 530028, China), AuthorCompanyExt(id=1324078106138517769, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, companyId=1324078106121740551, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.广西壮族自治区疾病预防控制中心慢性非传染性疾病防制所,广西 南宁 530028)]), AuthorCompany(id=1324078106205626634, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, xref=2., ext=[AuthorCompanyExt(id=1324078106218209547, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, companyId=1324078106205626634, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.广西壮族自治区疾病预防控制中心广西病毒性肝炎防治重点实验室)]), AuthorCompany(id=1324078106331455756, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, xref=3., ext=[AuthorCompanyExt(id=1324078106344038669, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, companyId=1324078106331455756, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.广西右江民族医学院公共卫生学院)])], figs=[ArticleFig(id=1324078110357987635, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, language=EN, label=Table 1, caption=

Univariate analysis of the association between sociodemographic characteristics and Diabetes Mellitus

, figureFileSmall=null, figureFileBig=null, tableContent=
研究变量人数构成比
(%)
糖尿病患者患病率
(%)
标化患病率(%)χ2值P值
性别12.3120.024
男2 68643.457221.315.3
女3 50156.654515.612.2
年龄(岁)271.750<0.001
18~441 24220.1907.26.9
45~592 02632.733216.415.3
≥602 91947.269523.824.7
居住地区0.5100.630
城市地区2 48640.250020.114.2
农村地区3 70159.861716.713.5
年人均收入(元)a42.1000.004
≤10 0001 56036.827217.417.5
>10 000~30 0002 20852.137917.211.5
>30 00046711.011524.616.8
民族2.1940.556
汉族3 81561.773519.313.8
壮族1 88830.531616.714.4
其他4847.86613.610.6
文化72.839<0.001
小学及以下2 93147.456719.317.6
初中1 73328.031918.415.4
高中/中专/技校89314.415917.811.9
大专及以上63010.27211.47.7
婚姻状况62.709<0.001
未婚3575.8359.86.5
已婚5 46988.499918.315.1
丧偶3064.97123.221.7
其他550.91221.812.1
职业129.754<0.001
农林牧渔水利业生产人员2 24636.337016.513.7
家务1 37522.225718.717.8
政府/事业单位61610.07011.46.9
退休人员3936.413033.131.7
商业服务2774.54415.99.5
其他1 28020.724619.215.4
BMI分类b105.241<0.001
正常体重2 97448.743014.59.6
低体重2944.83913.310.7
超重2 08434.145321.718.0
肥胖75312.319025.220.2
是否患有高血压c252.245<0.001
否3 37354.540812.18.8
是2 75444.570425.623.5
当前吸烟状况0.1260.970
从不吸烟4 64575.178716.913.7
现在吸烟1 29020.926720.714.0
已戒烟2524.16325.014.0
是否采取减盐措施2.6480.273
否3 84562.166817.413.3
是2 34237.944919.214.8
有害饮酒19.191<0.001
否6 04297.71 07017.713.5
是1452.34732.427.6
点外卖频率(次/月)12.7850.094
≤14 94679.989918.214.5
>1~55669.19216.314.0
>567510.912618.79.9
饮茶频率10.7240.232
几乎不3 98964.568617.213.3
偶尔94515.317518.515.7
经常4477.27316.310.7
每天80613.018322.715.7
喝咖啡频率12.7570.090
几乎不5 82194.11 05618.114.2
偶尔2654.34617.49.1
经常570.9915.85.3
每天440.7613.614.7
辛辣食物摄入频率35.3410.002
几乎不2 86646.351017.814.4
偶尔5368.78916.611.5
经常1 24120.119715.910.1
每天1 5442532120.817.6
睡觉时间(小时/天)26.3510.007
<71 56525.331420.118.4
7~93 94363.767117.012.5
>967911.013219.414.4
是否午睡d6.3760.109
否3 40155.158417.215.0
是2 77444.952919.112.8
), ArticleFig(id=1324078110462845236, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, language=CN, label=表1, caption=

不同社会人口学特征研究对象的糖尿病患病率

, figureFileSmall=null, figureFileBig=null, tableContent=
研究变量人数构成比
(%)
糖尿病患者患病率
(%)
标化患病率(%)χ2值P值
性别12.3120.024
男2 68643.457221.315.3
女3 50156.654515.612.2
年龄(岁)271.750<0.001
18~441 24220.1907.26.9
45~592 02632.733216.415.3
≥602 91947.269523.824.7
居住地区0.5100.630
城市地区2 48640.250020.114.2
农村地区3 70159.861716.713.5
年人均收入(元)a42.1000.004
≤10 0001 56036.827217.417.5
>10 000~30 0002 20852.137917.211.5
>30 00046711.011524.616.8
民族2.1940.556
汉族3 81561.773519.313.8
壮族1 88830.531616.714.4
其他4847.86613.610.6
文化72.839<0.001
小学及以下2 93147.456719.317.6
初中1 73328.031918.415.4
高中/中专/技校89314.415917.811.9
大专及以上63010.27211.47.7
婚姻状况62.709<0.001
未婚3575.8359.86.5
已婚5 46988.499918.315.1
丧偶3064.97123.221.7
其他550.91221.812.1
职业129.754<0.001
农林牧渔水利业生产人员2 24636.337016.513.7
家务1 37522.225718.717.8
政府/事业单位61610.07011.46.9
退休人员3936.413033.131.7
商业服务2774.54415.99.5
其他1 28020.724619.215.4
BMI分类b105.241<0.001
正常体重2 97448.743014.59.6
低体重2944.83913.310.7
超重2 08434.145321.718.0
肥胖75312.319025.220.2
是否患有高血压c252.245<0.001
否3 37354.540812.18.8
是2 75444.570425.623.5
当前吸烟状况0.1260.970
从不吸烟4 64575.178716.913.7
现在吸烟1 29020.926720.714.0
已戒烟2524.16325.014.0
是否采取减盐措施2.6480.273
否3 84562.166817.413.3
是2 34237.944919.214.8
有害饮酒19.191<0.001
否6 04297.71 07017.713.5
是1452.34732.427.6
点外卖频率(次/月)12.7850.094
≤14 94679.989918.214.5
>1~55669.19216.314.0
>567510.912618.79.9
饮茶频率10.7240.232
几乎不3 98964.568617.213.3
偶尔94515.317518.515.7
经常4477.27316.310.7
每天80613.018322.715.7
喝咖啡频率12.7570.090
几乎不5 82194.11 05618.114.2
偶尔2654.34617.49.1
经常570.9915.85.3
每天440.7613.614.7
辛辣食物摄入频率35.3410.002
几乎不2 86646.351017.814.4
偶尔5368.78916.611.5
经常1 24120.119715.910.1
每天1 5442532120.817.6
睡觉时间(小时/天)26.3510.007
<71 56525.331420.118.4
7~93 94363.767117.012.5
>967911.013219.414.4
是否午睡d6.3760.109
否3 40155.158417.215.0
是2 77444.952919.112.8
), ArticleFig(id=1324078110542537013, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, language=EN, label=Table 2, caption=

Variable coding for logistic regression analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
变量赋值
性别1=男;2=女
年龄(岁)1 =18~44;2 =45~59;3 = ≥60
年人均收入(元)1=≤10 000;2=>10 000~30 000;3=>30 000
文化1=小学及以下;2=初中;3=高中/中专/技校;4=大专及以上
婚姻状况1=未婚;2=已婚;3=丧偶;4=其他
职业1=农林牧渔水利业生产人员;2=家务;3=政府/事业单位;4=退休人员;5=商业服务;6=其他
BMI分类1 =体重正常;2=低体重;3 =超重;4 =肥胖
是否患有高血压0=否;1=是
有害饮酒0=否;1=是
辛辣食物摄入频率1 =几乎不;2=偶尔;3 =经常;4 =每天
睡觉时间(小时/天)1 =<7;2=7~9;3 =>9
), ArticleFig(id=1324078110618034486, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, language=CN, label=表2, caption=

logistic回归分析变量赋值情况

, figureFileSmall=null, figureFileBig=null, tableContent=
变量赋值
性别1=男;2=女
年龄(岁)1 =18~44;2 =45~59;3 = ≥60
年人均收入(元)1=≤10 000;2=>10 000~30 000;3=>30 000
文化1=小学及以下;2=初中;3=高中/中专/技校;4=大专及以上
婚姻状况1=未婚;2=已婚;3=丧偶;4=其他
职业1=农林牧渔水利业生产人员;2=家务;3=政府/事业单位;4=退休人员;5=商业服务;6=其他
BMI分类1 =体重正常;2=低体重;3 =超重;4 =肥胖
是否患有高血压0=否;1=是
有害饮酒0=否;1=是
辛辣食物摄入频率1 =几乎不;2=偶尔;3 =经常;4 =每天
睡觉时间(小时/天)1 =<7;2=7~9;3 =>9
), ArticleFig(id=1324078110706114871, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, language=EN, label=Table 3, caption=

Multivariate logistic regression analysis of Diabetes Mellitus

, figureFileSmall=null, figureFileBig=null, tableContent=
变量βSEWald χ2OR值(95%CI)P值
性别(ref:男)
女-0.240.152.480.788(0.586~1.060)0.115
年龄(岁)(ref:18~44)
45~590.810.288.182.249(1.290~3.919)0.004
≥601.230.3016.573.428(1.894~6.205)<0.001
年人均收入(元)(ref:≤10 000)
>10 000~30 000-0.450.177.470.635(0.459~0.880)0.006
>30 0000.180.240.561.198(0.745~1.927)0.455
文化(ref:小学及以下)
初中0.190.181.221.215(0.860~1.716)0.270
高中/中专/技校-0.020.240.000.985(0.618~1.568)0.948
大专及以上-0.050.370.020.951(0.458~1.976)0.893
婚姻状况(ref:未婚)
已婚0.030.490.001.030(0.390~2.717)0.952
丧偶-0.050.570.010.952(0.309~2.937)0.932
其他-0.200.710.080.818(0.203~3.297)0.778
职业(ref:农林牧渔水利业生产人员)
家务0.160.200.651.177(0.792~1.750)0.420
政府/事业单位-0.460.371.600.629(0.307~1.292)0.207
退休人员0.610.246.481.847(1.151~2.962)0.011
商业服务-0.420.351.460.655(0.330~1.302)0.228
其他0.350.222.621.425(0.928~2.191)0.106
BMI分类(ref:正常体重)
低体重0.230.400.341.261(0.577~2.753)0.561
超重0.730.1619.392.067(1.496~2.856)<0.001
肥胖0.840.2214.472.326(1.506~3.595)<0.001
是否患有高血压(ref:否)
是0.750.1622.122.110(1.546~2.880)<0.001
有害饮酒(ref:否)
是0.470.351.791.599(0.804~3.179)0.180
辛辣食物摄入频率(ref:几乎不)
偶尔-0.030.280.010.969(0.556~1.689)0.913
经常-0.180.220.700.831(0.539~1.282)0.403
每天0.020.190.011.017(0.701~1.477)0.929
睡觉时间(小时/天)(ref:<7)
7~9-0.040.160.080.956(0.705~1.297)0.774
>9-0.000.310.000.999(0.549~1.821)0.999
), ArticleFig(id=1324078110815166776, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078102531416322, language=CN, label=表3, caption=

糖尿病患病多因素logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量βSEWald χ2OR值(95%CI)P值
性别(ref:男)
女-0.240.152.480.788(0.586~1.060)0.115
年龄(岁)(ref:18~44)
45~590.810.288.182.249(1.290~3.919)0.004
≥601.230.3016.573.428(1.894~6.205)<0.001
年人均收入(元)(ref:≤10 000)
>10 000~30 000-0.450.177.470.635(0.459~0.880)0.006
>30 0000.180.240.561.198(0.745~1.927)0.455
文化(ref:小学及以下)
初中0.190.181.221.215(0.860~1.716)0.270
高中/中专/技校-0.020.240.000.985(0.618~1.568)0.948
大专及以上-0.050.370.020.951(0.458~1.976)0.893
婚姻状况(ref:未婚)
已婚0.030.490.001.030(0.390~2.717)0.952
丧偶-0.050.570.010.952(0.309~2.937)0.932
其他-0.200.710.080.818(0.203~3.297)0.778
职业(ref:农林牧渔水利业生产人员)
家务0.160.200.651.177(0.792~1.750)0.420
政府/事业单位-0.460.371.600.629(0.307~1.292)0.207
退休人员0.610.246.481.847(1.151~2.962)0.011
商业服务-0.420.351.460.655(0.330~1.302)0.228
其他0.350.222.621.425(0.928~2.191)0.106
BMI分类(ref:正常体重)
低体重0.230.400.341.261(0.577~2.753)0.561
超重0.730.1619.392.067(1.496~2.856)<0.001
肥胖0.840.2214.472.326(1.506~3.595)<0.001
是否患有高血压(ref:否)
是0.750.1622.122.110(1.546~2.880)<0.001
有害饮酒(ref:否)
是0.470.351.791.599(0.804~3.179)0.180
辛辣食物摄入频率(ref:几乎不)
偶尔-0.030.280.010.969(0.556~1.689)0.913
经常-0.180.220.700.831(0.539~1.282)0.403
每天0.020.190.011.017(0.701~1.477)0.929
睡觉时间(小时/天)(ref:<7)
7~9-0.040.160.080.956(0.705~1.297)0.774
>9-0.000.310.000.999(0.549~1.821)0.999
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广西2023年成年居民糖尿病流行现状及其影响因素分析
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黄金梅 1 , 蒋小云 1 , 唐美艳 3 , 滕有明 1 , 钟延旭 1, 2 , 毛玮 1
现代预防医学 | 疾病预防控制 2026,53(4): 741-746
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现代预防医学 |疾病预防控制 2026 , 53 (4) : 741 -746
广西2023年成年居民糖尿病流行现状及其影响因素分析
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黄金梅1, 蒋小云1, 唐美艳3, 滕有明1, 钟延旭1, 2 , 毛玮1
作者信息
  • 1.广西壮族自治区疾病预防控制中心慢性非传染性疾病防制所,广西 南宁 530028
  • 2.广西壮族自治区疾病预防控制中心广西病毒性肝炎防治重点实验室
  • 3.广西右江民族医学院公共卫生学院
通讯作者:
毛玮和钟延旭为共同通信作者。
毛玮,E-mail:
钟延旭,E-mail:
作者简介:

黄金梅和蒋小云为共同第一作者。

黄金梅(1984—),女,硕士,副主任医师,研究方向:慢性病防控

蒋小云(1996—),女,硕士,研究方向:慢性病防控

Analysis of the prevalence ofdiabetes mellitus and its influencing factors among adult residents, Guangxi, 2023
Jin-mei HUANG1, Xiao-yun JIANG1, Mei-yan TANG3, You-ming TENG1, Yan-xu ZHONG1, 2 , Wei MAO1
Affiliations
  • Department of Chronic Non-communicable Disease Prevention and Control, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi 530028, China
出版时间: 2026-02-25 doi: 10.20043/j.cnki.MPM.202510063
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目的

分析广西2023年成年居民糖尿病患病情况及其影响因素,为广西糖尿病精准防控提供科学依据。

方法

采用多阶段分层整群随机抽样,对广西18岁及以上居民进行问卷调查、身体测量和实验室检测,使用R 4.5.1软件进行χ2检验和logistic回归分析。

结果

在6 187人调查对象中,共有1 117人确定为糖尿病患者,糖尿病标化患病率为13.8%。多因素分析结果显示,年龄增长(与18~44岁相比,45~59岁:OR=2.249,95%CI : 1.290~3.919;60岁及以上:OR=3.428,95%CI : 1.894~6.205、退休人员(与农林牧渔水利业生产人员相比,OR=1.847,95%CI : 1.151~2.962),超重和肥胖(与正常体重相比,超重:OR=2.067,95%CI : 1.496~2.856;肥胖:OR=2.326,95%CI : 1.506~3.595)以及患有高血压(与未患高血压相比,OR=2.110,95%CI : 1.546~2.880)是糖尿病的危险因素。

结论

广西糖尿病患病率呈现快速上升趋势,需针对中老年人、超重或肥胖以及患有高血压等重点人群,实施精准防控。

糖尿病  /  患病率  /  影响因素
Objective

To analyze the prevalence and its influencing factors among adult residents in Guangxi in 2023, so as to provide scientific basis for accurate prevention and control of diabetes mellitus in Guangxi.

Methods

A multi-stage stratified cluster random sampling method was used to select residents aged 18 years and older in Guangxi. Participants completed questionnaires, physical examinations, and laboratory tests. Data were analyzed using R 4.5.1 software, including χ2 tests and multivariable logistic regression.

Results

Among the 6 187 subjects, 1 117 were identified as diabetic patients, with a standardized prevalence of diabetes 13.8 %. Multivariate analysis revealed that age (compared with 18-44 years old, 45-59 years old: OR=2.249, 95 % CI: 1.290-3.919; age 60 and above: OR = 3.428, 95 % CI: 1.894-6.205), retirees (compared with agricultural, forestry, animal husbandry, fishery and water conservancy production personnel, OR=1.847, 95 % CI: 1.151-2.962), overweight and obesity (compared with normal weight, overweight: OR=2.067, 95 % CI: 1.496-2.856; obesity: OR=2.326, 95 % CI: 1.506-3.595), and hypertension (compared with non-hypertensive individuals, OR=2.110, 95 % CI: 1.546-2.880) were significant risk factors for diabetes.

Conclusion

In 2023, the prevalence of diabetes in Guangxi showed a rapid rising trend. It is necessary to implement targeted prevention and control for key populations such as middle-aged and elderly people, overweight or obese people and individuals with hypertension.

Diabetes mellitus  /  Prevalence rate  /  Influencing factors
黄金梅, 蒋小云, 唐美艳, 滕有明, 钟延旭, 毛玮. 广西2023年成年居民糖尿病流行现状及其影响因素分析. 现代预防医学, 2026 , 53 (4) : 741 -746 . DOI: 10.20043/j.cnki.MPM.202510063
Jin-mei HUANG, Xiao-yun JIANG, Mei-yan TANG, You-ming TENG, Yan-xu ZHONG, Wei MAO. Analysis of the prevalence ofdiabetes mellitus and its influencing factors among adult residents, Guangxi, 2023[J]. Modern Preventive Medicine, 2026 , 53 (4) : 741 -746 . DOI: 10.20043/j.cnki.MPM.202510063
随着人口老龄化和生活方式的改变,人群糖尿病的患病情况日趋严重。根据《柳叶刀》杂志发布的2022年数据[1],全球糖尿病成年患者人数已超过8亿,较1990年相比增长四倍,患病率从7%增至14%。中国是全球糖尿病患者最多的国家,患病率已从1980年的不足1%升至2018年的12.4%[2]。糖尿病及其并发症患病率的激增,给社会带来沉重负担,且存在显著的地区和社会经济差异[3]。广西具有多元的民族构成、独特的地理环境、各异的生活方式以及发展不平衡的经济格局等区域特征,这些因素均可能对糖尿病在该地区的流行态势产生影响,然而目前仍缺乏关于广西糖尿病流行状况的最新数据。本研究基于广西2023年成年居民慢性病及其危险因素数据,分析糖尿病患病情况及其影响因素,以期为推动广西糖尿病精准防控工作提供科学依据。
本研究样本量采用公式进行计算。其中,置信水平取95%(双侧),相应的u=1.96,概率P取2018全国监测糖尿病患病率11.9%,设计效率deff值取为3,误差r=20%,d=20%×11.9%。根据以上参数取值,计算得到平均每一层的样本量约为2 133人。全国城乡2层,31个省,共计层数为62层,并考虑无应答率27%,计算得到总样本量约为18.1万人。全国共302个监测点,平均每个监测点应至少调查600人。2023年广西中国居民慢性病及其危险因素监测项目覆盖10个国家级监测点,根据中国居民慢性病及其危险因素监测工作方案,按照多阶段分层整群随机抽样方法,抽取10个县(区),随后每个县(区)随机抽取3个乡镇(街道),每个乡镇(街道)随机抽取2个行政村(居委会),每个行政村(居委会)抽取不少于45户居民进行调查,每个县(区)调查不少于600人,将18岁及以上自愿并能正常参与问卷调查的常住居民作为调查对象。本次共抽取调查对象6 670人,完成个人问卷6 231份,完成率93.42%,将因空腹血糖、服糖后2小时血糖和糖尿病诊断病史数据均缺失,无法根据糖尿病诊断标准判断是否为糖尿病患者的问卷视为无效问卷,并及时排除,最后有效问卷6 187份,问卷有效率为99.29%。本研究通过广西壮族自治区疾病预防控制中心伦理委员会审查(GXCDCIRB2023-0040),调查对象均知情同意。
包括调查对象的基本信息(性别、年龄、居住地区、收入、民族、文化等)、生活方式(吸烟、饮酒、睡觉时间等)、身高、体重、血压、血糖信息。
(1)糖尿病诊断标准:空腹血糖≥7.0 mmol/L和/或服糖后2小时血糖≥11.1 mmol/L和/或已被乡镇(社区)及以上级别医院确诊为糖尿病者[4]。(2)身体质量指数(BMI)的定义:BMI<18.5 kg/m2为低体重,18.5≤BMI<24.0 kg/m2为正常体重,24.0≤BMI<28.0 kg/m2为超重,BMI≥28.0 kg/m2为肥胖[4]。(3)高血压诊断标准:此次调查测得的平均收缩压≥140 mm Hg和(或)平均舒张压≥90 mm Hg,或经医生诊断为高血压且最近2周内正在服药[4]。(4)吸烟:分为从不吸烟、现在吸烟(包括每天或有时吸烟)和已戒烟(以前吸烟但现在不吸)[4]。(5)有害饮酒定义:男性日均酒精摄入量≥61 g,女性日均酒精摄入量≥41 g[4]。(6)饮茶、喝咖啡或辛辣食物摄入频率:分为几乎不(少于1天/月),偶尔(1~2天/周或1~3天/月),经常(3~6天/周),每天。
统计学分析采用R 4.5.1软件。为使分析结果具有可比性,使用2020年第七次人口普查数据确定权重系数,采用复杂抽样加权调整方法对结果进行标化处理。统计描述采用构成比和患病率指标,同时计算标化患病率;影响因素分析则采用基于复杂抽样设计的χ2检验和logistic回归模型,检验水准设定为α=0.05。
本研究共纳入6 187名18岁及以上成人,其中男性2 686人(43.4%),女性3 501人(56.6%),性别比为1:1.3;城市居民2 486人(40.2%),农村居民3 701人(59.8%);平均年龄为(56.75±14.37)岁。见表1。
实际调查人数为6 187人,确定为糖尿病患者共有1 117人,人群患病率为18.1%,标化患病率为13.8%。不同性别、年龄、年人均收入、文化、婚姻状况、职业、BMI分类、高血压患病情况、有害饮酒、辛辣食物摄入频率以及睡觉时间的成年居民,糖尿病标化患病率差异均具有统计学意义(P<0.05)。见表1。
以糖尿病患病情况(否=0,是=1)为因变量,以性别、年龄、年人均收入、文化、婚姻状况、职业、BMI分类、高血压患病情况、有害饮酒、辛辣食物摄入频率以及睡觉时间等因素为自变量,进行多因素logistic回归分析。结果显示,相比18~44岁,45~59岁和60岁及以上人群患病风险显著升高;相比年人均收入≤10 000元,年人均收入10 001~30 000元的人群患病风险较低;相较于农林牧渔水利业生产人员,退休人员患病风险较高;相比正常体重,超重和肥胖人群患病风险显著升高;与未患高血压相比,患有高血压会增加糖尿病患病风险。见表3。
本次调查结果显示,2023年广西成年居民人群糖尿病标化患病率为13.8%,与2023年海南省的患病率(13.7%)较为接近[5],低于吴晓宇等[6]调查的2023年全国平均水平(16.81%)和北方地区水平(17.94%),呈现北部和东部地区患病率明显高于南部和西部地区的现象。与2010年广西糖尿病患病率(7.1%)[7-8]相比,2023年患病率年均增长幅度已达5.24%,超过全国年均增幅(3.36%)[9],提示广西糖尿病患病率的快速增长态势应引起高度重视。
多因素分析显示,45岁及以上人群糖尿病患病风险显著高于18~44岁人群,与多项研究结果一致[10-12],可能与年龄相关的胰岛素抵抗增强、β细胞功能衰退及代谢能力下降有关[13]。年人均收入10 001~30 000元人群糖尿病患病风险低于人均收入≤10 000元人群,或受益于更均衡的饮食结构、生活方式、医疗可及性及心理状态等。相较于农林牧渔水利业生产人员,退休人员因年龄偏高,患病风险在职业中较高,与四川省报告一致[14]。超重和肥胖是糖尿病患病核心危险因素,患病风险显著高于正常体重[15-18]。其机制与脂肪堆积导致胰岛素抵抗与β细胞功能障碍相关,而减重可有效改善该状况[19]。2023年广西成年居民超重率和肥胖率标化前分别为34.1%、12.3%,标化后分别为31.8%、13.0%,均低于2018年全国平均水平(34.3%和16.4%)[20],但肥胖率与广西2010年(5.7%)[7]相比年均增长约6.55%,高于全国2012~2018年均增速(5.5%)[21]。控制体重是我国慢性病防控的重点,《健康中国行动(2019—2030年)》《“体重管理年”活动实施方案》等多项政策均强调体重管理的重要性,亟需推进落实以遏制糖尿病等疾病的快速增长。高血压患者罹患糖尿病的风险显著增高,可能与两种疾病共享遗传、代谢背景以及不良生活方式的叠加有关。研究表明,约44.77%的糖尿病患者患有高血压[22],提示协同防控的重要性。
本研究存在一定局限性,首先研究设计为横断面调查,无法确定因果关系;其次部分变量为自我报告,可能存在信息偏倚。
综上所述,2023年广西成年居民糖尿病标化患病率为13.8%,近年增长迅速,防控形势严峻。应重点加强对45岁及以上中老年人群,尤其是退休人群,以及超重、肥胖和高血压群体实施综合干预。
  • 广西医疗卫生适宜技术开发与推广应用项目(S2021066)
  • 广西壮族自治区疾病预防控制中心青年博士提升科研能力课题(22253988)
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2026年第53卷第4期
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doi: 10.20043/j.cnki.MPM.202510063
  • 接收时间:2025-10-10
  • 首发时间:2026-11-02
  • 出版时间:2026-02-25
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  • 收稿日期:2025-10-10
基金
广西医疗卫生适宜技术开发与推广应用项目(S2021066)
广西壮族自治区疾病预防控制中心青年博士提升科研能力课题(22253988)
作者信息
    1.广西壮族自治区疾病预防控制中心慢性非传染性疾病防制所,广西 南宁 530028
    2.广西壮族自治区疾病预防控制中心广西病毒性肝炎防治重点实验室
    3.广西右江民族医学院公共卫生学院

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毛玮和钟延旭为共同通信作者。
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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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