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Article(id=1311350427447288705, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202601167, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1768233600000, receivedDateStr=2026-01-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579905616, onlineDateStr=2026-09-28, pubDate=1786291200000, pubDateStr=2026-08-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579905616, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579905616, creator=13701087609, updateTime=1790579905616, updator=13701087609, issue=Issue{id=1311350193946194882, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='15', pageStart='2689', pageEnd='2880', issueExtLink='null', onlineDate='null', pubDate='1786291200000', pubDateStr='2026-08-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790579849945, creator='13701087609', updateTime=1790588319569, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311385718195315029, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311385718195315030, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311350193946194882, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2706, endPage=2712, ext={EN=ArticleExt(id=1311350427677975426, articleId=1311350427447288705, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Association between WBC-hsCRP inflammatory score and type 2 diabetes prevalence based on the CHARLS and NHANES databases, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

This study aims to investigate the association between an inflammatory score constructed from white blood cell (WBC) count and high-sensitivity C-reactive protein (hs-CRP) and the risk of type 2 diabetes mellitus (T2DM).

Methods

Using data from the China Health and Retirement Longitudinal Study (CHARLS) and the U.S. National Health and Nutrition Examination Survey (NHANES), this study performed logistic regression analyses, restricted cubic spline (RCS) analyses, and subgroup analyses to investigate the association between the WBC-hsCRP inflammatory score and T2DM.

Results

Logistic regression analyses indicated that higher WBC-hsCRP inflammatory scores were associated with increased odds of T2DM.After extensive adjustment for potential confounders, each interquartile-range (IQR) increase in the WBC-hsCRP inflammatory score was associated with a 12% and 45% higher odds of T2DM in CHARLS and NHANES, respectively (CHARLS: OR=1.12,95% CI: 1.05-1.19; NHANES: OR=1.45, 95% CI: 1.22-1.72). RCS analyses suggested a nonlinear association in CHARLS but an approximately linear association in NHANES. The robustness of these findings was further confirmed by subgroup analyses.

Conclusion

Our results indicate a positive association between the WBC-hsCRP inflammatory score and T2DM, suggesting its potential utility for identifying individuals at elevated risk of T2DM.

, authors=Yan TANG1, Jie HUI3, Yun-feng YU1, Wan-jia ZHANG1, Xue-rong WU1, Rong YU2, authorsList=Yan TANG, Jie HUI, Yun-feng YU, Wan-jia ZHANG, Xue-rong WU, Rong YU, authorCompany=null, correspAuthors=Rong YU, 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=1311350432253961105, articleId=1311350427447288705, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=基于CHARLS与NHANES数据库的白细胞计数-高敏C反应蛋白炎症评分与2型糖尿病患病关联研究, columnId=1228016567632462653, journalTitle=现代预防医学, columnName=流行病与统计方法, runingTitle=null, highlight=null, articleAbstract=
目的

探讨白细胞计数（white blood cell count，WBC）和高敏C反应蛋白（high-sensitivity C-reactive protein，hs-CRP）构建的炎症评分与2型糖尿病 （type 2 diabetes mellitus,T2DM）发病风险之间的关联。

方法

基于中国健康与退休纵向研究（China Health and Retirement Longitudinal Study，CHARLS）和美国国家健康与营养调查（U.S. National Health and Nutrition Examination Survey，NHANES）的数据，本研究采用logistic回归分析、限制性立方样条（restricted cubic spline，RCS）分析以及亚组分析，探究WBC-hsCRP炎症评分与T2DM的关联性。

结果

Logistic回归分析显示，较高的WBC-hsCRP炎症评分与T2DM发生风险增加相关。经广泛校正潜在混杂因素后，WBC-hsCRP炎症评分每增加一个四分位距（IQR），CHARLS和NHANES的T2DM发生风险分别增加12%和45%（CHARLS：OR=1.12,95%CI：1.05～1.19；NHANES：OR=1.45,95%CI：1.22～1.72）。RCS分析表明CHARLS存在非线性关联，而NHANES呈现近似线性关联。亚组分析进一步验证了这些结果的稳健性。

结论

本研究结果提示WBC-hsCRP炎症评分与T2DM呈正相关，提示其在识别T2DM高风险个体方面具有潜在应用价值。

, authors=唐燕1, 惠杰3, 俞赟丰1, 张万佳1, 吴雪榕1, 喻嵘2, authorsList=唐燕, 惠杰, 俞赟丰, 张万佳, 吴雪榕, 喻嵘, authorCompany=null, correspAuthors=喻嵘, authorNote=

唐燕（2001—），女，硕士在读，研究方向：内分泌疾病的中医药防治

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喻嵘，E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=MI/5MEPZ/ueWOxKBc2oolA==, magXml=JabtgcNAtEi70bDbOuHtiQ==, pdfUrl=null, pdf=pjFGMFTEovO8UXtUqa4apw==, pdfFileSize=864280, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=FXoIUfSgcngerD2BIwcypw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=rACAkwjQOKOeBqyyJDUXQw==, mapNumber=null, fund=null)}, authors=[Author(id=1311350433034101658, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1311350433138959260, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, authorId=1311350433034101658, language=EN, stringName=Yan TANG, firstName=Yan, middleName=null, lastName=TANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410007, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1311350433235428253, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, authorId=1311350433034101658, language=CN, stringName=唐燕, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1.湖南中医药大学第一附属医院，湖南 长沙 410007, bio={"content":"

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Mediators of Inflammation, 2022,2022: 3706508., articleTitle=Role of C-Reactive protein in diabetic inflammation, refAbstract=null), Reference(id=1311350442546783216, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, doi=null, pmid=null, pmcid=null, year=2024, volume=15, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[28], rfOrder=27, authorNames=Zhou HH, Tang YL, Xu TH, journalName=Frontiers in Immunology, refType=null, unstructuredReference=Zhou HH, Tang YL, Xu TH, et al. 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注：实线代表OR的参考值，灰色带状区域代表95%置信区间；校正了年龄、性别、婚姻状况、教育水平、吸烟状况、饮酒状况、高血压、BMI、甘油三酯、总胆固醇、低密度脂蛋白、高密度脂蛋白、肾小球滤过率、血尿素氮、尿酸、血小板计数；图A为CHARLS；图B为NHANES。

, figureFileSmall=Txjkxh2k1SeE1FuWk9XTMg==, figureFileBig=GzcZAFjekpVK+MnWS+1Erg==, tableContent=null), ArticleFig(id=1311350437807219657, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, language=EN, label=Figure 3, caption=Subgroup analysis for the association of WBC-hsCRP inflammatory score with T2DM, figureFileSmall=qcJvVbS55RXxlMaRPcacUQ==, figureFileBig=yb7LzUHqiyexbAjkWfLx2A==, tableContent=null), ArticleFig(id=1311350437882717130, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, language=CN, label=图3, caption=WBC-hsCRP炎症评分与T2DM关联的亚组分析

注：图A为CHARLS；图B为NHANES。

, figureFileSmall=qcJvVbS55RXxlMaRPcacUQ==, figureFileBig=yb7LzUHqiyexbAjkWfLx2A==, tableContent=null), ArticleFig(id=1311350437945631691, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, language=EN, label=Table 1, caption=

Clinical characteristics of participants from CHARLS database ［（）， n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群（n=6 546）非T2DM组（n=5 741）T2DM组（n=805）P值
年龄（岁）58.1±8.558.1±8.658.1±8.10.646
性别0.110
男2 830 (43)2 503 (44)327 (41)
女3 716 (57)3 238 (56)478 (59)
婚姻状况0.911
已婚5 880 (90)5 156 (90)724 (90)
其他666 (10)585 (10)81 (10)
教育程度0.457
高中以下5 913 (90)5 180 (90)733 (91)
高中或以上633 (10)561 (10)72 (9)
吸烟状况0.005
是2 384 (36)2 127 (37)257 (32)
否4 162 (64)3 614 (63)548 (68)
饮酒状况0.007
是1 925 (29)1 721 (30)204 (25)
否4 621 (71)4 020 (70)601 (75)
高血压<0.001
是2 549 (39)2 137 (37)412 (51)
否3 997 (61)3 604 (63)393 (49)
BMI(kg/m2)24.2±32.424.0±34.625.4±4.0<0.001
甘油三酯（mg/dl）*129.5±91.8124.6±86.7164.4±116.7<0.001
总胆固醇(mg/dl)*193.9±37.9192.9±37.6201.0±39.1<0.001
低密度脂蛋白(mg/dl)*117.3±34.5116.7±33.9121.4±38.3<0.001
高密度脂蛋白(mg/dl)*51.2±14.751.9±14.746.3±13.8<0.001
肾小球滤过率[ml/(min·1.73m2)]93.3±13.993.4±13.892.6±14.70.214
血尿素氮(mg/dl)*15.6±4.415.6±4.415.6±4.20.897
尿酸(mg/dl)*4.4±1.24.3±1.24.5±1.3<0.001
血小板（1 000 个细胞/μl）212.9±75.6212.6±76.3215.0±70.80.191
WBC-hsCRP炎症评分0.2±1.10.2±1.10.4±1.2<0.001
), ArticleFig(id=1311350438025323468, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, language=CN, label=表1, caption=

CHARLS数据库纳入人群的临床特征［（）， n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群（n=6 546）非T2DM组（n=5 741）T2DM组（n=805）P值
年龄（岁）58.1±8.558.1±8.658.1±8.10.646
性别0.110
男2 830 (43)2 503 (44)327 (41)
女3 716 (57)3 238 (56)478 (59)
婚姻状况0.911
已婚5 880 (90)5 156 (90)724 (90)
其他666 (10)585 (10)81 (10)
教育程度0.457
高中以下5 913 (90)5 180 (90)733 (91)
高中或以上633 (10)561 (10)72 (9)
吸烟状况0.005
是2 384 (36)2 127 (37)257 (32)
否4 162 (64)3 614 (63)548 (68)
饮酒状况0.007
是1 925 (29)1 721 (30)204 (25)
否4 621 (71)4 020 (70)601 (75)
高血压<0.001
是2 549 (39)2 137 (37)412 (51)
否3 997 (61)3 604 (63)393 (49)
BMI(kg/m2)24.2±32.424.0±34.625.4±4.0<0.001
甘油三酯（mg/dl）*129.5±91.8124.6±86.7164.4±116.7<0.001
总胆固醇(mg/dl)*193.9±37.9192.9±37.6201.0±39.1<0.001
低密度脂蛋白(mg/dl)*117.3±34.5116.7±33.9121.4±38.3<0.001
高密度脂蛋白(mg/dl)*51.2±14.751.9±14.746.3±13.8<0.001
肾小球滤过率[ml/(min·1.73m2)]93.3±13.993.4±13.892.6±14.70.214
血尿素氮(mg/dl)*15.6±4.415.6±4.415.6±4.20.897
尿酸(mg/dl)*4.4±1.24.3±1.24.5±1.3<0.001
血小板（1 000 个细胞/μl）212.9±75.6212.6±76.3215.0±70.80.191
WBC-hsCRP炎症评分0.2±1.10.2±1.10.4±1.2<0.001
), ArticleFig(id=1311350438105015245, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, language=EN, label=Table 2, caption=

Clinical characteristics of participants from NHANES database ［（）， n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群
（n=3 472）		非T2DM组
（n=2 359）		T2DM组
（n=1 113）		P值
年龄（岁）61.1±10.160.21± 10.163.7±9.9<0.001
性别0.005
男1 720 (47)1 123 (45)597 (53)
女1 752 (53)1 236 (55)516 (47)
婚姻状况0.020
已婚2 072 (65)1 412 (67)660 (61)
其他1 400 (35)947 (33)453 (39)
教育程度<0.001
高中以下773 (13)445 (11)328 (19)
高中或以上2 699 (87)1 914 (89)785 (81)
吸烟状况0.524
是1 691 (49)1 138 (48)553 (50)
否1 781 (51)1 221 (52)560 (50)
饮酒状况<0.001
是2 851 (86)1 963 (87)888 (81)
否621 (14)396 (13)225 (19)
高血压<0.001
是1 800 (46)1 035 (39)765 (67)
否1 672 (54)1 324 (61)348 (33)
BMI(kg/m2)29.8±6.629.0±6.232.2±7.1<0.001
甘油三酯（mg/dl）*117.8±86.6110.9±86.3138.5±84.2<0.001
总胆固醇(mg/dl)*193.4±42.5199.0±39.6176.4±46.5<0.001
低密度脂蛋白(mg/dl)*112.5±37.9117.1±35.698.8±41.4<0.001
高密度脂蛋白(mg/dl)*56.5±18.558.8±18.149.7±17.9<0.001
肾小球滤过率[ml/(min·1.73m2)]83.9±18.884.7±17.581.4±22.10.056
血尿素氮(mg/dl)*16.1±5.815.6±5.217.6±7.2<0.001
尿酸(mg/dl)*5.5±1.45.4±1.35.7±1.60.001
血小板（1 000 个细胞/μl）232.6±61.1233.7±61.0229.4±61.30.078
WBC-hsCRP炎症评分-0.2±1.0-0.3±1.00.1±0.8<0.001
), ArticleFig(id=1311350438205678542, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, language=CN, label=表2, caption=

NHANES数据库纳入人群的临床特征［（）， n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群
（n=3 472）		非T2DM组
（n=2 359）		T2DM组
（n=1 113）		P值
年龄（岁）61.1±10.160.21± 10.163.7±9.9<0.001
性别0.005
男1 720 (47)1 123 (45)597 (53)
女1 752 (53)1 236 (55)516 (47)
婚姻状况0.020
已婚2 072 (65)1 412 (67)660 (61)
其他1 400 (35)947 (33)453 (39)
教育程度<0.001
高中以下773 (13)445 (11)328 (19)
高中或以上2 699 (87)1 914 (89)785 (81)
吸烟状况0.524
是1 691 (49)1 138 (48)553 (50)
否1 781 (51)1 221 (52)560 (50)
饮酒状况<0.001
是2 851 (86)1 963 (87)888 (81)
否621 (14)396 (13)225 (19)
高血压<0.001
是1 800 (46)1 035 (39)765 (67)
否1 672 (54)1 324 (61)348 (33)
BMI(kg/m2)29.8±6.629.0±6.232.2±7.1<0.001
甘油三酯（mg/dl）*117.8±86.6110.9±86.3138.5±84.2<0.001
总胆固醇(mg/dl)*193.4±42.5199.0±39.6176.4±46.5<0.001
低密度脂蛋白(mg/dl)*112.5±37.9117.1±35.698.8±41.4<0.001
高密度脂蛋白(mg/dl)*56.5±18.558.8±18.149.7±17.9<0.001
肾小球滤过率[ml/(min·1.73m2)]83.9±18.884.7±17.581.4±22.10.056
血尿素氮(mg/dl)*16.1±5.815.6±5.217.6±7.2<0.001
尿酸(mg/dl)*5.5±1.45.4±1.35.7±1.60.001
血小板（1 000 个细胞/μl）232.6±61.1233.7±61.0229.4±61.30.078
WBC-hsCRP炎症评分-0.2±1.0-0.3±1.00.1±0.8<0.001
), ArticleFig(id=1311350438310536143, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, language=EN, label=Table 3, caption=

Logistic regression analysis of the association between WBC-hsCRP inflammatory score and T2DM

, figureFileSmall=null, figureFileBig=null, tableContent=
WBC-hsCRP炎症评分模型 1模型 2模型 3
OR(95%CI)P值OR(95%CI)P值OR(95%CI)P值
CHARLS
每增加一个四分位距1.14(1.08～1.21)<0.0011.15(1.08～1.21)<0.0011.12(1.05～1.19)<0.001
Q1RefRefRef
Q21.18(0.94～1.48)0.2001.19(0.95～1.50)0.1301.10(0.87～1.39)0.400
Q31.54(1.24～1.92)<0.0011.55(1.25～1.93)<0.0011.33(1.06～1.67)0.015
Q41.76(1.42～2.18)<0.0011.79(1.45～2.22)<0.0011.51(1.21～1.90)<0.001
趋势P值<0.001<0.001<0.001
NHANES
每增加一个四分位距1.73(1.50～2.00)<0.0011.72(1.48～2.01)<0.0011.45(1.22～1.72)<0.001
Q1RefRefRef
Q21.27(0.87～1.84)0.2001.25(0.87～1.81)0.2001.13(0.77～1.67)0.500
Q32.58(1.87～3.54)<0.0012.44(1.77～3.35)<0.0011.84(1.26～2.68)0.015
Q43.61(2.64～4.94)<0.0013.70(2.70～5.07)<0.0012.45(1.67～3.60)<0.001
趋势P值<0.001<0.001<0.001
), ArticleFig(id=1311350438381839312, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311350427447288705, language=CN, label=表3, caption=

WBC-hsCRP炎症评分与T2DM的logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
WBC-hsCRP炎症评分模型 1模型 2模型 3
OR(95%CI)P值OR(95%CI)P值OR(95%CI)P值
CHARLS
每增加一个四分位距1.14(1.08～1.21)<0.0011.15(1.08～1.21)<0.0011.12(1.05～1.19)<0.001
Q1RefRefRef
Q21.18(0.94～1.48)0.2001.19(0.95～1.50)0.1301.10(0.87～1.39)0.400
Q31.54(1.24～1.92)<0.0011.55(1.25～1.93)<0.0011.33(1.06～1.67)0.015
Q41.76(1.42～2.18)<0.0011.79(1.45～2.22)<0.0011.51(1.21～1.90)<0.001
趋势P值<0.001<0.001<0.001
NHANES
每增加一个四分位距1.73(1.50～2.00)<0.0011.72(1.48～2.01)<0.0011.45(1.22～1.72)<0.001
Q1RefRefRef
Q21.27(0.87～1.84)0.2001.25(0.87～1.81)0.2001.13(0.77～1.67)0.500
Q32.58(1.87～3.54)<0.0012.44(1.77～3.35)<0.0011.84(1.26～2.68)0.015
Q43.61(2.64～4.94)<0.0013.70(2.70～5.07)<0.0012.45(1.67～3.60)<0.001
趋势P值<0.001<0.001<0.001
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基于CHARLS与NHANES数据库的白细胞计数-高敏C反应蛋白炎症评分与2型糖尿病患病关联研究
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唐燕 1 , 惠杰 3 , 俞赟丰 1 , 张万佳 1 , 吴雪榕 1 , 喻嵘 2
现代预防医学 | 流行病与统计方法 2026,53(15): 2706-2712
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现代预防医学 |流行病与统计方法 2026 , 53 (15) : 2706 -2712
基于CHARLS与NHANES数据库的白细胞计数-高敏C反应蛋白炎症评分与2型糖尿病患病关联研究
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唐燕1, 惠杰3, 俞赟丰1, 张万佳1, 吴雪榕1, 喻嵘2
作者信息
  • 1.湖南中医药大学第一附属医院，湖南 长沙 410007
  • 2.湖南中医药大学中医学院，湖南 长沙 410208
  • 3.广州中医药大学第八临床医学院
通讯作者:
喻嵘，E-mail:
作者简介:

唐燕（2001—），女，硕士在读，研究方向：内分泌疾病的中医药防治

Association between WBC-hsCRP inflammatory score and type 2 diabetes prevalence based on the CHARLS and NHANES databases
Yan TANG1, Jie HUI3, Yun-feng YU1, Wan-jia ZHANG1, Xue-rong WU1, Rong YU2
Affiliations
  • The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410007, China
出版时间: 2026-08-10 doi: 10.20043/j.cnki.MPM.202601167
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摘要
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目的

探讨白细胞计数（white blood cell count，WBC）和高敏C反应蛋白（high-sensitivity C-reactive protein，hs-CRP）构建的炎症评分与2型糖尿病 （type 2 diabetes mellitus,T2DM）发病风险之间的关联。

方法

基于中国健康与退休纵向研究（China Health and Retirement Longitudinal Study，CHARLS）和美国国家健康与营养调查（U.S. National Health and Nutrition Examination Survey，NHANES）的数据，本研究采用logistic回归分析、限制性立方样条（restricted cubic spline，RCS）分析以及亚组分析，探究WBC-hsCRP炎症评分与T2DM的关联性。

结果

Logistic回归分析显示，较高的WBC-hsCRP炎症评分与T2DM发生风险增加相关。经广泛校正潜在混杂因素后，WBC-hsCRP炎症评分每增加一个四分位距（IQR），CHARLS和NHANES的T2DM发生风险分别增加12%和45%（CHARLS：OR=1.12,95%CI：1.05～1.19；NHANES：OR=1.45,95%CI：1.22～1.72）。RCS分析表明CHARLS存在非线性关联，而NHANES呈现近似线性关联。亚组分析进一步验证了这些结果的稳健性。

结论

本研究结果提示WBC-hsCRP炎症评分与T2DM呈正相关，提示其在识别T2DM高风险个体方面具有潜在应用价值。

白细胞-高敏C反应蛋白炎症评分  /  T2DM  /  国家健康与营养调查  /  中国纵向健康与退休纵向研究
Objective

This study aims to investigate the association between an inflammatory score constructed from white blood cell (WBC) count and high-sensitivity C-reactive protein (hs-CRP) and the risk of type 2 diabetes mellitus (T2DM).

Methods

Using data from the China Health and Retirement Longitudinal Study (CHARLS) and the U.S. National Health and Nutrition Examination Survey (NHANES), this study performed logistic regression analyses, restricted cubic spline (RCS) analyses, and subgroup analyses to investigate the association between the WBC-hsCRP inflammatory score and T2DM.

Results

Logistic regression analyses indicated that higher WBC-hsCRP inflammatory scores were associated with increased odds of T2DM.After extensive adjustment for potential confounders, each interquartile-range (IQR) increase in the WBC-hsCRP inflammatory score was associated with a 12% and 45% higher odds of T2DM in CHARLS and NHANES, respectively (CHARLS: OR=1.12,95% CI: 1.05-1.19; NHANES: OR=1.45, 95% CI: 1.22-1.72). RCS analyses suggested a nonlinear association in CHARLS but an approximately linear association in NHANES. The robustness of these findings was further confirmed by subgroup analyses.

Conclusion

Our results indicate a positive association between the WBC-hsCRP inflammatory score and T2DM, suggesting its potential utility for identifying individuals at elevated risk of T2DM.

WBC-hsCRP inflammatory score  /  Type 2 diabetes  /  NHANES  /  CHARLS
唐燕, 惠杰, 俞赟丰, 张万佳, 吴雪榕, 喻嵘. 基于CHARLS与NHANES数据库的白细胞计数-高敏C反应蛋白炎症评分与2型糖尿病患病关联研究. 现代预防医学, 2026 , 53 (15) : 2706 -2712 . DOI: 10.20043/j.cnki.MPM.202601167
Yan TANG, Jie HUI, Yun-feng YU, Wan-jia ZHANG, Xue-rong WU, Rong YU. Association between WBC-hsCRP inflammatory score and type 2 diabetes prevalence based on the CHARLS and NHANES databases[J]. Modern Preventive Medicine, 2026 , 53 (15) : 2706 -2712 . DOI: 10.20043/j.cnki.MPM.202601167
正文
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2型糖尿病（type 2 diabetes mellitus,T2DM）是一种以胰岛素抵抗和胰岛素相对缺乏为特征的慢性代谢疾病[1-2]。根据国际糖尿病联合会的数据，目前全球糖尿病患者5.37亿，其中近95%为T2DM[3]。糖尿病已成为全球公共卫生的重要挑战，尤其在中低收入国家[4]。然而，全球近45%的糖尿病患者尚未被诊断出来[5]。因此，识别高危人群的风险因素对于疾病的预防至关重要。糖尿病的主要病理生理机制涉及β细胞功能衰竭、胰岛素抵抗、糖代谢紊乱及炎症反应[6]。其中炎症一直是糖尿病相关研究的焦点。近年来，中性粒细胞与淋巴细胞比值（neutrophil to lymphocyte ratio, NLR）、血小板与淋巴细胞比值（platelet to lymphocyte ratio, PLR）、全身炎症反应指数（systemic inflammation response index, SIRI）等复合炎症标志物在预测糖尿病及其并发症风险方面展现出潜力，有望成为简便可靠的辅助评估指标[7]。
白细胞计数（white blood cell count，WBC）-超敏C反应蛋白（high-sensitivity C-reative protein，hs-CRP）炎症评分通过计算WBC计数和hs-CRP水平的Z评分并求和得出[8]。与单个炎症标志物相比，WBC-hsCRP炎症评分不仅能更系统化地反映身体炎症负荷，还具备数据易获取、计算简便等优势[9]。既往研究证实了WBC-hsCRP炎症评分与代谢性疾病、心血管疾病及癌症风险之间的关联[8-10]。然而，目前还没有研究探讨WBC-hsCRP炎症评分与T2DM患病风险之间的关联。本研究利用中国健康与养老追踪调查（China Health and Retirement Longitudinal Study,CHARLS）和美国国家健康与营养检查调查（U.S. National Heaithand Nutrition Examination Surey，NHANES）这两个具有全国代表性的数据库，在不同人群与不同研究设计背景下验证WBC-hsCRP炎症评分与T2DM关联方向的一致性，以期对T2DM患者的治疗提供指导。
1　对象与方法
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1.1　数据来源
在2015年之前，NHANES数据库中提供的是常规C反应蛋白（C-reative protein，CRP）数据。为实现与CHARLS数据库中hs-CRP数据统一，本研究的数据来源于NHANES2015—2020年周期和CHARLS2011及2020年两波周期。筛选流程见图1。
1.2　暴露和结局变量
根据每个参与者的WBC和hs-CRP生物标志物水平（X）、平均值（M）以及标准差（SD），可以计算出其Z分数。具体计算公式为：Z分数=(X-M) / SD。WBC-hsCRP炎症评分通过将WBC和hs-CRP的Z分数相加来计算[8]。评分每增加1分，近似对应“WBC或hs-CRP中任一指标较总体均值升高约1个标准差”或“两者较均值同时升高”的综合效应。
在CHARLS研究中，2020年波次缺少T2DM的血检数据。因此T2DM的诊断基于自我报告的数据以及是否服用抗T2DM药物。当受访者既往被医生诊断出患有T2DM或者受访者平素服用降糖药时，他们被归类为T2DM患者。
在NHANES研究中，T2DM是根据以下标准定义的：（1）空腹血糖水平≥7 mmol/L；（2）糖化血红蛋白水平≥6.5%；（3）随机血糖≥11.1 mmol/L；（4）餐后2 h血糖≥11.1 mmol/L。满足其中任何一个标准即可诊断为T2DM。当以上数值缺失或未达到糖尿病诊断标准时，自报T2DM相关信息（自我报告的诊断；使用胰岛素；使用降糖药物）中的任意一项满足也可以被定义为患有T2DM[11]。
1.3　协变量
本研究纳入了可能影响WBC-hsCRP炎症评分与T2DM患病风险关联的协变量[10,12]。人口学特征包括年龄、性别、婚姻状况。社会经济因素包括教育水平。健康行为因素包括吸烟状态及饮酒状态。健康状况因素包括高血压。人体测量和代谢参数包括身体质量指数（body mass index,BMI）、甘油三酯、总胆固醇、低密度脂蛋白、高密度脂蛋白、肾小球滤过率、尿素氮、尿酸、血小板计数。纳入这些协变量旨在控制潜在的混杂效应，确保模型估计的稳健性，从而更准确地评估WBC-hsCRP炎症评分与T2DM风险之间的关联。
1.4　统计方法
考虑到CHARLS与NHANES在研究设计、抽样方案、结局判定方式及变量测量背景等方面存在差异，本研究未进行跨数据库合并分析，而是进行了两个数据库并行独立分析。对于CHARLS数据库，连续变量以（均数±标准差）表示，分类变量以频数和百分比呈现，采用两独立样本t检验和χ2检验评估组间差异。在NHANES中，按照国家卫生统计中心的建议，所有分析都采用了加权方法。连续变量报告为（加权均数±标准差），分类变量报告为频数和加权百分比。组间比较采用了设计校正的加权t检验和Rao-Scott校正χ2检验。采用logistic回归分析评估WBC-hsCRP炎症评分与T2DM患病风险之间的关联。进行趋势检验，以分析WBC-hsCRP炎症评分与T2DM风险之间是否存在剂量-反应关系。探索WBC-hsCRP炎症评分与T2DM风险之间潜在的非线性关联，并绘制剂量反应曲线。最后，开展亚组分析以评估潜在效应修饰因素。所有统计分析均使R 4.4.2进行分析，检验水准α=0.05。研究比较重点包括：关联方向的一致性、效应量大小以及剂量-反应关系的形态。
2　结果
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2.1　研究人群的基线特征
在CHARLS队列中，分析了6 546名符合纳入标准的参与者，其中805人被诊断为T2DM，5 741人未患有T2DM。与未患T2DM的人群相比，T2DM患者有高血压病史、BMI偏高。在临床指标方面，T2DM组的个体呈现出甘油三酯、总胆固醇、低密度脂蛋白、尿酸、WBC-hsCRP炎症评分等水平显著升高，而高密度脂蛋白水平显著降低（均P<0.05）。见表1。
本研究共纳入了3 472名NHANES参与者。其中，1 113名受试者符合T2DM诊断标准，2 359人未患有T2DM。与未患T2DM的受试者相比，T2DM患者通常年龄较大、男性占比高、已婚、大多为高中以下学历、多有高血压病史、BMI较高。在临床指标方面，T2DM患者呈现出甘油三酯、血尿素氮、尿酸、WBC-hsCRP炎症评分等水平较高以及总胆固醇、低密度脂蛋白、高密度脂蛋白水平较低（均P<0.05）。见表2。
2.2　炎症评分与T2DM风险的关联
Logistic回归分析的结果如表3所示。在CHARLS队列中，当WBC-hsCRP炎症评分为连续变量时，未调整混杂因素的模型1显示，WBC-hsCRP炎症评分每增加一个四分位距，T2DM患病的风险就升高14%，OR为1.14。在进一步调整混杂因素的模型2和模型3中，该关联仍然显著，OR分别为1.15和1.12。将WBC-hsCRP炎症评分按四分位数分组后，与最低四分位（Q1）相比，最高四分位（Q4）在三个模型中均表现出T2DM风险显著升高（OR>1）。尽管Q2组的风险升高在三个模型中均未达到统计学显著性，但整体趋势依然显著。在NHANES中观察到类似结果，当WBC-hsCRP炎症评分为连续变量时，三个模型均显示炎症评分升高与T2DM风险增加显著相关；将WBC-hsCRP炎症评分作为分类变量分析时，在完全调整模型中，炎症评分位于Q3和Q4的T2DM患病风险相较Q1分别增加84%和145%（OR=1.84与2.45）。
CHARLS和NHANES的趋势检验均表明WBC-hsCRP炎症评分与T2DM风险之间存在显著的剂量-反应关系。为进一步评估其剂量-反应模式及潜在非线性关系，本研究进行了RCS分析。结果显示，WBC-hsCRP炎症评分与T2DM患病之间的剂量-反应关系在两个数据库中均呈正向趋势，但曲线形态存在差异。在CHARLS中该关联为非线性（P for nonlinearity=0.012），而NHANES中该关联整体表现为近似线性（P for nonlinearity=0.256）。见图2。
2.3　亚组分析
如图3所示，本研究按年龄、性别、婚姻状况、教育水平、吸烟、饮酒、高血压及BMI类别等因素进行了亚组分析，评估WBC-hsCRP炎症评分与T2DM风险之间的关联。结果显示，无论是CHARLS还是NHANES,在大多数亚组中，较高的WBC-hsCRP炎症评分均与T2DM风险升高显著相关（P<0.05），且效应方向一致，提示该关联在不同人群特征中具有稳健性。交互作用分析发现，在CHARLS数据中，性别、吸烟状况和高血压对WBC-hsCRP炎症评分与T2DM的关联存在显著交互作用，提示该关联强度在上述亚组间可能存在差异；相比之下，在NHANES各亚组中未观察到统计学显著交互作用。
3　讨论
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本研究使用CHARLS和NHANES数据库评估了WBC-hsCRP炎症评分与T2DM患病之间的关联。研究发现如下：（1）logistic回归分析表明，WBC-hsCRP炎症评分与T2DM风险呈正相关。（2）RCS分析显示，在CHARLS队列中，两者的关联符合非线性关系；而在NHANES队列中，两者为线性关系。（3）亚组分析发现，在CHARLS数据中，性别、吸烟状况和高血压对WBC-hsCRP炎症评分与T2DM的关联存在显著交互作用。
尽管CHARLS和NHANES的RCS分析曲线形态不同，但两者的结果在方向上高度一致，即WBC-hsCRP炎症评分升高均与T2DM患病风险增加相关。既往研究显示，在相同BMI水平下，东亚人群较西方人群更易累积内脏和异位脂肪，并呈现更不利的脂肪组织炎症特征，从而可能使其胰岛素敏感性和β细胞功能更易受到损害[13-14]。此外，多项研究表明，不同种族和地区的人群在肠道菌群组成及代谢产物方面存在显著差异，而这些差异与肥胖、胰岛素抵抗及糖尿病风险密切相关[15-17]。这些发现不仅揭示了WBC-hsCRP炎症评分-T2DM关系的复杂性，也强调在制定预防策略时需要考虑种族特异性和地区差异。在CHARLS的交互作用分析中，高血压影响WBC-hsCRP炎症评分与T2DM患病之间的关联强度。既往证据表明，高血压通常伴随更高的炎症负荷与胰岛素抵抗背景，因而更易放大炎症对糖代谢稳态的不利影响[18]。然而，在NHANES中未观察到一致的交互作用，因此上述发现更适合作为提示性结果，为后续在不同人群中开展验证研究提供线索。
近年来，许多研究探讨了WBC、hs‐CRP和T2DM风险之间的关联。例如，一项韩国的随访研究报道，较高四分位数的白细胞计数组在基线调查后10年内显示显着更高的T2DM发病率[19]。一项基于挪威人群的队列研究显示，基线hs-CRP处于最高三分位者相较最低三分位，发生T2DM的风险增加73%[20]。这些研究主要分析了WBC、hs-CRP这两个单一炎症标志物与T2DM风险的关联，不足以反映体内的整体炎症水平。因此，本研究利用WBC-hsCRP炎症评分将两者结合起来，从而更全面地反映机体的炎症负荷。
WBC-hsCRP炎症评分与T2DM的正相关关联可能涉及以下生物学机制：在慢性炎症状态下，外周白细胞被激活并分泌TNF-α和IL-1β等促炎细胞因子[21-22]，这些促炎细胞因子可以通过激活一系列的激酶（如JNK和IKKβ），促使胰岛素受体底物的丝氨酸磷酸化，并削弱其正常的酪氨酸磷酸化反应[23-24]。这个过程破坏了胰岛素信号的正常传导，导致细胞对胰岛素的敏感性下降，即产生胰岛素抵抗[25]。此外，中性粒细胞在释放胞外诱捕网（neutrophil extracellular traps, NETs）的同时，伴随着活性氧的过量生成，可增强炎症级联反应并造成氧化应激负荷增加，使β细胞功能受损，从而与胰岛素信号受损及胰岛素抵抗的加重相关[26]。另一方面，在肥胖与慢性低度炎症背景下，脂肪细胞产生TNF-α和IL-6刺激肝脏持续合成CRP，使机体处于炎症应激状态[27]。除此之外，CRP沉积于局部的单体构象能显著放大炎症与促凝状态，通过间接损害β细胞功能与加剧糖脂代谢紊乱，共同推动T2DM病程的进展[28]。故探讨WBC-hsCRP炎症评分与T2DM的关系具有一定的理论依据。
然而，本研究也有以下局限性：一是，由于数据来自公共数据库，缺乏对数据质量和研究参与者背景信息的控制。二是，这项研究仅涉及45岁及以上的中美两国人，研究结论在其他人群中的适用性尚不明确。为了解决这些局限性，还需要更多证据来揭示WBC-hsCRP炎症评分与T2DM之间的联系。
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  • 国家自然科学基金面上项目(82074400)
  • 湖南省自然科学基金创新研究群体项目(2024JJ1007)
  • 湖南中医药大学学科建设“揭榜挂帅”项目(22JBZ002)
  • 湖南中医药大学研究生创新课题(2025CX130)
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参考文献 引证文献
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2026年第53卷第15期
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doi: 10.20043/j.cnki.MPM.202601167
  • 接收时间：2026-01-13
  • 首发时间：2026-09-28
  • 出版时间：2026-08-10
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  • 收稿日期：2026-01-13
基金
国家自然科学基金面上项目(82074400)
湖南省自然科学基金创新研究群体项目(2024JJ1007)
湖南中医药大学学科建设“揭榜挂帅”项目(22JBZ002)
湖南中医药大学研究生创新课题(2025CX130)
作者信息
    1.湖南中医药大学第一附属医院，湖南 长沙 410007
    2.湖南中医药大学中医学院，湖南 长沙 410208
    3.广州中医药大学第八临床医学院

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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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