Article(id=1240395015743132275, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240395006914130733, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202412359, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1734624000000, receivedDateStr=2024-12-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773662817177, onlineDateStr=2026-03-16, pubDate=1753372800000, pubDateStr=2025-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773662817177, onlineIssueDateStr=2026-03-16, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773662817177, creator=13701087609, updateTime=1773662817177, updator=13701087609, issue=Issue{id=1240395006914130733, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='14', pageStart='2497', pageEnd='2688', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1773662815073, creator=13701087609, updateTime=1773662858015, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240395187109810535, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240395006914130733, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240395187109810536, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240395006914130733, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2658, endPage=2663, ext={EN=ArticleExt(id=1240395016032539273, articleId=1240395015743132275, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=A g-formula-based study of the effect of depressive symptoms on the risk of developing type 2 diabetes mellitus in Chinese middle-aged and elderly people, columnId=1228016573156360233, journalTitle=Modern Preventive Medicine, columnName=Disease Control and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the effect of depressive symptoms on the risk of developing type 2 diabetes mellitus in middle-aged and elderly people in China.

Methods

Based on the data from the China Health and Retirement Longitudinal Study (CHARLS) 2011 and 2018, 9 697 middle-aged and elderly people aged 45 years or older were included as study subjects. Chained equations were used to perform g-formula analysis after multiple interpolation of missing values of covariates, and stratified analyses were performed to explore the association between depressive symptoms and the risk of developing type 2 diabetes mellitus with respect to age and gender.

Results

The results of the analysis after multiple interpolation of covariates and adjustment for confounding showedthat the mean risk of developing type 2 diabetes mellitus in study participants with depressive symptoms which was 1.3 times higher than that of those without depressive symptoms [RR(95% CI):1.37(1.15-1.62)], with a mean hazard difference of 0.02. Those with mild depressive symptoms had a mean risk of type 2 diabetes mellitus of 1.27 times higher than that of those without depressive symptoms [RR(95% CI):1.27(1.07-1.52)], with a mean difference of 0.01; those with severe depressive symptoms had a mean risk of developing type 2 diabetes mellitus that was 2.22 times higher than that of those who were not depressed [RR(95% CI):2.22(1.64-3.00)]; the mean difference was 0.06.

Conclusion

Depressive symptoms and the risk of type 2 diabetes mellitus were significantly associated with the risk of developing type 2 diabetes mellitus among middle-aged and elderly people in China. Associated with the risk of developing type 2 diabetes, the risk of developing the disease increased with the severity of depressive symptoms.

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目的

探究中国中老年人抑郁症状对2型糖尿病发病风险的影响。

方法

基于中国健康与养老追踪调查(CHARLS)2011年、2018年的数据,纳入9 697名45岁以上中老年人作为研究对象。采用链式方程对协变量缺失值进行多重插补后进行g-formula分析,并对年龄、性别作分层分析探究抑郁症状与2型糖尿病发病风险的关联。

结果

多重插补协变量、调整混杂后的分析结果显示,有抑郁症状的研究对象患2型糖尿病的平均风险是无抑郁症状者的1.37倍[RR(95% CI):1.37(1.15~1.62)],平均危险度差值为0.02。其中轻度抑郁症状者患2型糖尿病的平均风险是无抑郁者的1.27倍[RR(95% CI):1.27(1.07~1.52)],平均差异为0.01;重度抑郁症状者患2型糖尿病的平均风险是无抑郁者的2.22倍[RR(95% CI):2.22(1.64~3.00)];平均差异为0.06。

结论

中国中老年人群的抑郁症状与2型糖尿病发病风险显著相关,且发病风险随抑郁症状严重程度的加重而增加。

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郭冰,E-mail:
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肖心怡(2002—),女,本科在读,研究方向:流行病与卫生统计学

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Comprehensive Physiology, 2025, 15(1): e70003., articleTitle=Type 2 diabetes mellitus: a comprehensive review of pathophysiology, comorbidities, and emerging therapies, refAbstract=null), Reference(id=1240413548506051463, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395015743132275, doi=null, pmid=null, pmcid=null, year=2025, volume=365, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[24], rfOrder=31, authorNames=Guan YT, Liu GQ, Tang FM, journalName=Life Sciences, refType=null, unstructuredReference=Guan YT, Liu GQ, Tang FM, et al. Stress hyperglycemia in acute pancreatitis: From mechanisms to prognostic implications[J]. 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注:调整的协变量包括年龄、户籍、性别、婚姻状况、教育水平、BMI、高血压、高血脂、吸烟、饮酒、自评健康、生活水平、每日进食次数,在不同分层中不含分层因素本身;RR: RiskRatio; RD: RiskDifference。

, figureFileSmall=jkV3snPL2cNiYxWubdtGIg==, figureFileBig=LQO3awr1D3/dJDytD7tkcg==, tableContent=null), ArticleFig(id=1240413540826280531, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395015743132275, language=EN, label=Table 1, caption=

Baseline survey of different sociodemographic characteristics and depression

, figureFileSmall=null, figureFileBig=null, tableContent=
变量人数比例(%)无抑郁人数(%)有抑郁人数(%)P
性别<0.001
4 58047.23 291(52.6)1 289(37.4)
5 11752.82 961(47.4)2 156(62.6)
年龄(岁)<0.001
45~647 63778.85 000(80.0)2 637(76.5)
≥652 06021.21 252(20.0)808(23.5)
户籍<0.001
农村7 86981.14 838(77.4)3 031(88.0)
城市1 82818.91 414(22.6)414(12.0)
教育水平<0.001
小学及以下6 39165.93 750(60.0)2 641(76.7)
中学2 91230.02 164(34.6)748(21.7)
大专及以上3944.1338(5.4)56(1.6)
婚姻状况<0.001
已婚8 68289.55 747(91.9)2 935(85.2)
其他101510.5505(8.1)510(14.8)
吸烟<0.001
3 79039.12 614(41.8)1 176(34.1)
5 90760.93 638(58.2)2 269(65.9)
饮酒<0.001
>1次/月2 50325.81 787(28.6)716(20.8)
≤1次/月7858.1539(8.6)246(7.1)
6 40966.13 926(62.8)2 483(72.1)
自评健康<0.001
非常好3303.4289(4.6)41(1.2)
很好1 29813.41 079(17.3)219(6.4)
3 26533.72 382(38.1)883(25.6)
一般3 47135.82 015(32.2)1 456(42.3)
1 33313.7487(7.8)846(24.6)
高血压<0.001
1 99720.61 212(19.4)785(22.8)
7 70079.45 040(80.6)2 660(77.2)
血脂异常0.311
6827.0427(6.8)255(7.4)
9 01593.05 825(93.2)3 190(92.6)
BMI(kg/m2<0.001
<18.57928.2430(6.9)362(10.5)
18.5~24.96 18563.83 963(63.4)2 222(64.5)
25~29.92 06021.21 411(22.6)649(18.8)
≥306606.8448(7.2)212(6.2)
生活水平<0.001
非常高180.215(0.2)3(0.1)
偏上2702.8214(3.4)56(1.6)
中等5 18353.43 714(59.4)1 469(42.6)
偏下3 10032.01 857(29.7)1 243(36.1)
贫困1 12611.6452(7.2)674(19.6)
每日进食次数<0.001
≥41481.5102(1.6)46(1.3)
38 26585.25 488(87.8)2 777(80.6)
21 27013.1658(10.5)612(17.8)
≤1140.14(0.1)10(0.3)
), ArticleFig(id=1240413540952109660, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395015743132275, language=CN, label=表1, caption=

基线调查不同社会人口学特征与抑郁情况

, figureFileSmall=null, figureFileBig=null, tableContent=
变量人数比例(%)无抑郁人数(%)有抑郁人数(%)P
性别<0.001
4 58047.23 291(52.6)1 289(37.4)
5 11752.82 961(47.4)2 156(62.6)
年龄(岁)<0.001
45~647 63778.85 000(80.0)2 637(76.5)
≥652 06021.21 252(20.0)808(23.5)
户籍<0.001
农村7 86981.14 838(77.4)3 031(88.0)
城市1 82818.91 414(22.6)414(12.0)
教育水平<0.001
小学及以下6 39165.93 750(60.0)2 641(76.7)
中学2 91230.02 164(34.6)748(21.7)
大专及以上3944.1338(5.4)56(1.6)
婚姻状况<0.001
已婚8 68289.55 747(91.9)2 935(85.2)
其他101510.5505(8.1)510(14.8)
吸烟<0.001
3 79039.12 614(41.8)1 176(34.1)
5 90760.93 638(58.2)2 269(65.9)
饮酒<0.001
>1次/月2 50325.81 787(28.6)716(20.8)
≤1次/月7858.1539(8.6)246(7.1)
6 40966.13 926(62.8)2 483(72.1)
自评健康<0.001
非常好3303.4289(4.6)41(1.2)
很好1 29813.41 079(17.3)219(6.4)
3 26533.72 382(38.1)883(25.6)
一般3 47135.82 015(32.2)1 456(42.3)
1 33313.7487(7.8)846(24.6)
高血压<0.001
1 99720.61 212(19.4)785(22.8)
7 70079.45 040(80.6)2 660(77.2)
血脂异常0.311
6827.0427(6.8)255(7.4)
9 01593.05 825(93.2)3 190(92.6)
BMI(kg/m2<0.001
<18.57928.2430(6.9)362(10.5)
18.5~24.96 18563.83 963(63.4)2 222(64.5)
25~29.92 06021.21 411(22.6)649(18.8)
≥306606.8448(7.2)212(6.2)
生活水平<0.001
非常高180.215(0.2)3(0.1)
偏上2702.8214(3.4)56(1.6)
中等5 18353.43 714(59.4)1 469(42.6)
偏下3 10032.01 857(29.7)1 243(36.1)
贫困1 12611.6452(7.2)674(19.6)
每日进食次数<0.001
≥41481.5102(1.6)46(1.3)
38 26585.25 488(87.8)2 777(80.6)
21 27013.1658(10.5)612(17.8)
≤1140.14(0.1)10(0.3)
), ArticleFig(id=1240413541056967268, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395015743132275, language=EN, label=Table 2, caption=

Rates and differences in risk of developing type 2 diabetes across depressive symptoms

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变量发病数/个体数RR(95% CI)RD(95% CI)
抑郁症状
310/6 2521.000.00
228/3 4451.37(1.15~1.62)0.02(0.01~0.03)
抑郁症状程度
310/6 2521.000.00
轻度182/2 9721.27(1.07~1.52)0.01(0.00~0.02)
重度46/472.22(1.64~3.00)0.06(0.03~0.09)
), ArticleFig(id=1240413541207962223, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240395015743132275, language=CN, label=表2, caption=

不同抑郁症状下2型糖尿病发病风险的比率和差异

, figureFileSmall=null, figureFileBig=null, tableContent=
变量发病数/个体数RR(95% CI)RD(95% CI)
抑郁症状
310/6 2521.000.00
228/3 4451.37(1.15~1.62)0.02(0.01~0.03)
抑郁症状程度
310/6 2521.000.00
轻度182/2 9721.27(1.07~1.52)0.01(0.00~0.02)
重度46/472.22(1.64~3.00)0.06(0.03~0.09)
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基于g-formula的中国中老年人抑郁症状对2型糖尿病发病风险的影响研究
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肖心怡 , 牟明军 , 曾文倩 , 郭冰
现代预防医学 | 疾病预防控制 2025,52(14): 2658-2663
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现代预防医学 | 疾病预防控制 2025, 52(14): 2658-2663
基于g-formula的中国中老年人抑郁症状对2型糖尿病发病风险的影响研究
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肖心怡, 牟明军, 曾文倩, 郭冰
作者信息
  • 四川大学华西公共卫生学院/四川大学华西第四医院,流行病与卫生统计学系,四川 成都 610041
  • 肖心怡(2002—),女,本科在读,研究方向:流行病与卫生统计学

通讯作者:

郭冰,E-mail:
A g-formula-based study of the effect of depressive symptoms on the risk of developing type 2 diabetes mellitus in Chinese middle-aged and elderly people
Xin-yi XIAO, Ming-jun MOU, Wen-qian ZENG, Bing GUO
Affiliations
  • West China School of Public Health, Sichuan University/West China Fourth Hospital, Sichuan University Department of Epidemiology and Health Statistics, Chengdu, Sichuan 610041, China
出版时间: 2025-07-25 doi: 10.20043/j.cnki.MPM.202412359
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目的

探究中国中老年人抑郁症状对2型糖尿病发病风险的影响。

方法

基于中国健康与养老追踪调查(CHARLS)2011年、2018年的数据,纳入9 697名45岁以上中老年人作为研究对象。采用链式方程对协变量缺失值进行多重插补后进行g-formula分析,并对年龄、性别作分层分析探究抑郁症状与2型糖尿病发病风险的关联。

结果

多重插补协变量、调整混杂后的分析结果显示,有抑郁症状的研究对象患2型糖尿病的平均风险是无抑郁症状者的1.37倍[RR(95% CI):1.37(1.15~1.62)],平均危险度差值为0.02。其中轻度抑郁症状者患2型糖尿病的平均风险是无抑郁者的1.27倍[RR(95% CI):1.27(1.07~1.52)],平均差异为0.01;重度抑郁症状者患2型糖尿病的平均风险是无抑郁者的2.22倍[RR(95% CI):2.22(1.64~3.00)];平均差异为0.06。

结论

中国中老年人群的抑郁症状与2型糖尿病发病风险显著相关,且发病风险随抑郁症状严重程度的加重而增加。

抑郁症状  /  2型糖尿病  /  中老年人  /  g-formula
Objective

To investigate the effect of depressive symptoms on the risk of developing type 2 diabetes mellitus in middle-aged and elderly people in China.

Methods

Based on the data from the China Health and Retirement Longitudinal Study (CHARLS) 2011 and 2018, 9 697 middle-aged and elderly people aged 45 years or older were included as study subjects. Chained equations were used to perform g-formula analysis after multiple interpolation of missing values of covariates, and stratified analyses were performed to explore the association between depressive symptoms and the risk of developing type 2 diabetes mellitus with respect to age and gender.

Results

The results of the analysis after multiple interpolation of covariates and adjustment for confounding showedthat the mean risk of developing type 2 diabetes mellitus in study participants with depressive symptoms which was 1.3 times higher than that of those without depressive symptoms [RR(95% CI):1.37(1.15-1.62)], with a mean hazard difference of 0.02. Those with mild depressive symptoms had a mean risk of type 2 diabetes mellitus of 1.27 times higher than that of those without depressive symptoms [RR(95% CI):1.27(1.07-1.52)], with a mean difference of 0.01; those with severe depressive symptoms had a mean risk of developing type 2 diabetes mellitus that was 2.22 times higher than that of those who were not depressed [RR(95% CI):2.22(1.64-3.00)]; the mean difference was 0.06.

Conclusion

Depressive symptoms and the risk of type 2 diabetes mellitus were significantly associated with the risk of developing type 2 diabetes mellitus among middle-aged and elderly people in China. Associated with the risk of developing type 2 diabetes, the risk of developing the disease increased with the severity of depressive symptoms.

Depressive symptoms  /  Type 2 diabetes  /  Middle-aged and elderly adults  /  G-formula
肖心怡, 牟明军, 曾文倩, 郭冰. 基于g-formula的中国中老年人抑郁症状对2型糖尿病发病风险的影响研究. 现代预防医学, 2025 , 52 (14) : 2658 -2663 . DOI: 10.20043/j.cnki.MPM.202412359
Xin-yi XIAO, Ming-jun MOU, Wen-qian ZENG, Bing GUO. A g-formula-based study of the effect of depressive symptoms on the risk of developing type 2 diabetes mellitus in Chinese middle-aged and elderly people[J]. Modern Preventive Medicine, 2025 , 52 (14) : 2658 -2663 . DOI: 10.20043/j.cnki.MPM.202412359
糖尿病严重影响我国居民健康水平,已成为亟需解决的重要公共卫生问题。2011年至2021,十年间我国的糖尿病患者数量从9 000万增加至1.4亿,增长率高达56%[1]。我国糖尿病人群绝大部分为2型糖尿病患者,约占90%[2],其中中老年人群糖尿病和糖尿病前期患病率约为10%和40%[3],因此中老年人群是糖尿病的防控关键人群。根据生物-心理-社会的医学模式,糖尿病的发生发展与心理因素紧密相关。目前糖尿病和抑郁的关联研究主要集中于探讨糖尿病与抑郁症的共患情况、糖尿病对抑郁症发病风险的影响。既往研究显示,抑郁症作为糖尿病的常见合并症之一,我国一项横断面研究发现2型糖尿病患者中抑郁症患病率为16%[4]。此外,一项荟萃分析显示,相较于未患糖尿病的人群,2型糖尿病患者面临更高的抑郁风险[5]。然而,目前关于抑郁对糖尿病的影响的相关研究较少。一项针对糖尿病患者的研究发现,糖尿病患者并发抑郁会导致其自我效能的降低,造成血糖管理障碍[6],进一步加速糖尿病的发展恶化。
此外,相较于既往研究主要使用的传统回归方法,g-formula方法可通过模拟不同的暴露情景预测该情境下可能发生的反事实结局,并计算标准化发生风险率,避免了传统回归方法可能出现的过度调整偏差;同时,当模型正确设定时,g-formula的有效性和稳定性高于传统回归方法[7-8]
综上所述,目前对糖尿病和抑郁的关联研究中,有关抑郁症状对糖尿病发病风险影响的研究较少,其中针对我国中老年人群的相关研究尚存在不足。因此,本研究基于g-formula分析探讨中国中老年人群的抑郁症状对2型糖尿病发病风险的影响。
本研究数据来自中国健康与养老追踪调查(CHARLS)[9]跨时8年的两次调查(2011年、2018年)。CHARLS调查采用多阶段概率比例规模抽样的方法,在县、村、家户、个人四个层面随机抽样,覆盖全国28个省份的150个县、450个社区(村),收集45岁以上中国中老年人的相关数据资料。根据研究目的,制定以下纳入标准:①2011年调查时年龄≥45岁;②关键变量(两次调查的2型糖尿病患病情况、2011年的抑郁评分)信息完整。排除标准:①2011年基线调查时已患2型糖尿病的个体;②脑损伤或智力障碍的个体(图1)。
CHARLS调查问卷运用中文版流行病学研究中心抑郁量表(CES-D10)评估抑郁症状情况。该量表分为两类共10个问题:第一类为8个关于负面消极情绪的问题,涵盖因小事烦恼、难以集中注意力、情绪低落、做事困难、恐惧感、睡眠障碍、孤独感及生活无法继续等方面;第二类为2个关于正面积极情绪的问题,涉及对未来是否充满希望及是否感到愉快。本研究根据2011年基线调查结果对抑郁症状进行测量:每个问题的回答按4分制赋分(0~3分),积极情绪问题反向赋分,所有问题得分的总和记为总分,总分范围0~30分[10]。按照既往研究中抑郁症状的检出率标准[11],若低于10分,则认为无抑郁症状;若10分及以上,则认为有抑郁症状。为了进一步分析抑郁症状的严重程度对结局的影响,对抑郁症状进一步细分:10~20分为轻度抑郁症状,21~30分为重度抑郁症状[12]
参考《中国2型糖尿病防治指南》(2020年版)[2],血糖升高(空腹血糖≥7.0 mmol/L、糖耐量试验2 h血糖≥11.1 mmol/L)或糖化血红蛋白≥6.5%;既往诊断过糖尿病或目前正在接受降糖治疗等均可作为诊断2型糖尿病的依据。CHARLS调查问卷中通过“是否有医生曾经告诉过您有糖尿病或血糖升高(包括糖耐量异常和空腹血糖升高)”来评估调查对象的2型糖尿病患病情况。本研究以2018年随访的2型糖尿病发病情况作为结局事件。
根据既往文献资料[6,13-14],抑郁症状和2型糖尿病关联中的混杂变量可能包括年龄、户籍、性别、婚姻状况、教育水平、体重指数(BMI)、高血压、血脂异常、吸烟、饮酒、自评健康、生活水平、每日进食次数等。因此本研究将2011年调查所收集的上述变量作为协变量纳入分析模型。BMI计算方式为BMI[体重(公斤)/身高(米)2]/体重(公斤)]。根据世界卫生组织(WHO)的标准,将BMI进一步划分为体重过轻(<18.5)、正常范围(18.5~24.9)、超重(25~29.9)、肥胖(≥30)四类。根据CHARLS的数据特点,经济状况以生活水平作为衡量指标,“总体来说,您怎么评价您自己家的生活水平?是非常高、偏上、中等、偏下还是贫困?”,由此分为五类;饮食因素以每日进食次数作为衡量指标,“您一般每天吃几顿饭?每天多于4顿,每天4顿,每天3顿,每天2顿,每天一顿,每天少于一顿”,分为≥4顿、3顿、2顿、≤1顿四类。
分类资料通过频数和构成比N(%)来表示,其中无序分类资料采用χ2检验进行组间比较、有序分类资料采用Kruskal-wallis H检验进行组间比较。对服从正态分布的计量资料,采用均数±标准差()的形式来表示,两组间的比较使用T检验,而多组间的比较则采用单因素方差分析(ANOVA)。采用链式方程对协变量的缺失值进行多重插补[15],将插补后的完整数据集用于后续分析。
对多重插补后的完整数据集进行g-formula分析[8],后续对年龄、性别作分层分析。g-formula方法可概述为两个步骤:首先,采用参数化模型对协变量、暴露和结局建模;然后,使用蒙特卡洛模拟评估不同暴露下的结局风险[7-8]。本研究中,根据结局变量类型采用logistic模型作为参数化模型,由此计算不同暴露下的风险值并标化处理,最终得到平均风险值以及平均风险差。以上模型均设定双侧检验水平α=0.05。本研究采用R 4.2.2软件进行统计分析。
根据纳入排除标准,本研究共纳入45岁及以上的中老年人9 697名,其中男性4 580名(47.2%)、女性5 117名(52.8%);抑郁症状3 445例。根据有无抑郁症状分组,经检验,性别、年龄、户籍、婚姻状况、教育水平、吸烟、饮酒、自评健康、高血压、BMI、生活水平、每日进食次数在两组均有显著差异,具体结果见表1
本研究以抑郁症状为自变量,2型糖尿病为因变量,对年龄、户籍、性别、婚姻状况、教育水平、BMI、高血压、血脂异常、吸烟、饮酒、自评健康、生活水平、每日进食次数等协变量的缺失值进行多重插补并做g-formula分析,分析结果见表2。在随访调查中,共有538例新发2型糖尿病,有抑郁症状的研究对象中共228例,其中轻度抑郁症状组中182例,重度抑郁症状组中46例。g-formula结果显示,有抑郁症状的研究对象患2型糖尿病的平均风险是无抑郁症状者的1.37倍[RR(95% CI):1.37(1.15~1.62)],平均风险差值为0.02[RD(95% CI): 0.02(0.01~0.03)]。其中轻度抑郁症状者患2型糖尿病的平均风险是无抑郁者的1.27倍[RR(95% CI):1.27(1.07~1.52)],平均风险差异为0.01;重度抑郁症状者患2型糖尿病的平均风险是无抑郁者的2.22倍[RR(95% CI):2.22(1.64~3.00)],平均风险差异为0.06。
在年龄分层分析中,中年组新发2型糖尿病430例,老年组新发2型糖尿病108例。多重插补并调整后的分析结果显示(图2),老年人抑郁症状与2型糖尿病发病的关联更为敏感(RR=1.60,95% CI:1.09~2.35),平均差异为0.03。在性别分层分析中,男性新发2型糖尿病236例,女性新发2型糖尿病302例。多重插补并调整后的分析结果显示,男性与女性的抑郁症状对2型糖尿病发病风险的影响相近。
中老年人群2型糖尿病患病率较高,须采取多维度、针对性强的综合干预措施进行防控。本研究结果提示,我国45岁及以上的中老年人群2型糖尿病患病率约为7.09%,与既往研究相近[16]。此外,研究还发现中老年人抑郁症状检出率高达30.26%,与另一项研究的31.26%[17]相近,表明抑郁症状在中老年人群中的发生率呈现出较高的水平。这可能是由中老年人身体机能逐渐下降、社交活跃度下降、经历压力性生活事件等多方面因素所致。
研究结果显示,中老年人的抑郁症状对2型糖尿病发病有显著影响。多重插补并调整性别、年龄等协变量后的g-formula分析显示,与无抑郁症状人群相比,有抑郁症状的中老年人更可能发生糖尿病[RR=1.37(1.15~1.62)]。这与Maina等人[14]的双样本双向孟德尔随机化研究结果一致,与Gaston等人[18]的研究发现儿童创伤增加2型糖尿病发病风险一致。抑郁症与2型糖尿病之间存在着复杂的潜在联系,这一联系涉及多个生理和心理机制。长时间的抑郁症状往往导致不健康的生活方式,如身体活动的减少[19]、不良饮食方式[20]以及睡眠障碍等。上述不健康的行为可能影响代谢、免疫系统,促使血糖水平升高。更深层次地,长期的抑郁状态还通过内分泌和炎症因子等途径对血糖调节产生直接影响。具体而言,抑郁会激活下丘脑-垂体-肾上腺(HPA)轴,导致一系列激素反映,包括促肾上腺皮质激素释放激素(CRH)和促肾上腺皮质激素(ACTH)的分泌增加,进而使皮质醇、儿茶酚胺和炎症标志物等物质浓度慢性升高[21]。这些变化会干扰正常的血糖调节机制[22]。值得注意的是,胰岛素抵抗被认为是2型糖尿病的关键致病因素。在糖尿病前期,为应对血糖浓度的升高,胰岛素水平会相应升高。然而,随着机体对胰岛素敏感度的下降,胰岛素调节血糖的能力逐渐减退,导致胰岛素水平逐步升高,最终引发慢性高胰岛素血症和高血糖,以致诱发胰岛β细胞衰竭,导致2型糖尿病的发生[23]。而抑郁状态下的激素变化,特别是皮质醇和儿茶酚胺的长期升高,会进一步加剧胰岛素抵抗的病理改变[24]。总而言之,抑郁症不仅通过不健康的生活方式间接影响血糖水平,还通过直接的生理机制对血糖调节产生负面影响,从而增加2型糖尿病的风险。
本研究对中老年人群中抑郁症状与2型糖尿病发病风险的关系进行了深入的年龄和性别分层分析。首先,在年龄分层方面,研究发现相较于中年人,老年人出现抑郁症状后更易发展为2型糖尿病。这一差异可能与老年人内分泌系统稳态的脆弱性增加以及胰岛β细胞储量的生理性减少等生理因素有关。其次,在性别分层分析中,研究结果显示男性与女性的抑郁症状与2型糖尿病发病的关联性相似。这意味着在中老年人群中,抑郁症状与2型糖尿病发病的关系可能较少受到性别因素的影响。
本研究存在一定的局限性。首先,研究基于我国CHARLS数据,虽然这是一个大规模的全国性调查,但样本的代表性可能仍受到一定限制,可能影响结果的普遍性和可推广性。其次,研究变量测量的测量和评估可能存在一定的主观性和测量误差,本研究所采用的变量来自CHARLS调查对象的自我报告,存在一定的信息偏倚。例如,2型糖尿病确定方式未包括血糖检测等生化指标,可能会低估2型糖尿病的患病情况。此外,研究采用了链式方程对协变量缺失值进行多重插补,虽然这是一种常用的处理缺失数据的方法,但插补过程本身可能引入一定的偏差或不确定性。
综上所述,本研究利用CHARLS纵向数据,探究了中国中老年人群抑郁症状与2型糖尿病发病风险之间的关系。结果显示,抑郁症状与2型糖尿病发病风险显著相关,且这种风险随着抑郁症状严重程度的增加而升高。这一发现提示,在寻求降低中老年人2型糖尿病发病风险的策略时,关注并改善其心理健康状况,特别是减少抑郁情绪,可能是一个重要的切入点。
  • 国家重点研发计划(2023YFC3605600; 2023YFC3605601)
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doi: 10.20043/j.cnki.MPM.202412359
  • 接收时间:2024-12-20
  • 首发时间:2026-03-16
  • 出版时间:2025-07-25
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  • 收稿日期:2024-12-20
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国家重点研发计划(2023YFC3605600; 2023YFC3605601)
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    四川大学华西公共卫生学院/四川大学华西第四医院,流行病与卫生统计学系,四川 成都 610041

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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