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Article(id=1324078382715117652, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202507233, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1752336000000, receivedDateStr=2025-07-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793614486626, onlineDateStr=2026-11-02, pubDate=1767974400000, pubDateStr=2026-01-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793614486626, onlineIssueDateStr=2026-11-02, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793614486626, creator=13701087609, updateTime=1793614486626, updator=13701087609, issue=Issue{id=1324078333767594037, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='1', pageStart='1', pageEnd='192', issueExtLink='null', onlineDate='null', pubDate='1767974400000', pubDateStr='2026-01-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1793614474956, creator='13701087609', updateTime=1793614571752, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1324078739914621270, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1324078739914621271, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1324078333767594037, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=7, endPage=12, ext={EN=ArticleExt(id=1324078383142936661, articleId=1324078382715117652, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Hemoglobin-to-red cell distribution width ratio and diabetes mellitus:a cross-sectional analysis of NHANES database, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=
Objective

This study aims to explore the association between the hemoglobin-to-red blood cell distribution width ratio (HRR) and the risk of diabetes mellitus (DM).

Methods

A total of 16 392 participants from the 2001—2020 National Health and Nutrition Examination Survey(NHANES) database were selected for this study. Logistic regression, subgroup analysis, and restricted cubic splin (RCS) analysis were applied to investigate the relationship between HRR and DM.

Results

The mean HRR among the included participants was 0.27±0.98, with diabetic patients showing significantly lower HRR compared to the control group (P<0.001). Logistic regression analysis revealed that when HRR was modeled as a continuous variable, for each standard deviation increase in HRR, the risk of DM decreased by 11% (OR=0.89, 95% CI: 0.84-0.95). When HRR was treated as a categorical variable based on quartiles, the highest fourth quartile(Q4) consistently showed a significant reduction in DM risk compared to the lowest quartile (Q1) across all three models (OR<1). Subgroup analysis demonstrated that increased HRR was associated with a reduced risk of DM in most subgroups, with most P-values<0.05. The dose-response analysis indicated a linear negative correlation between HRR and the risk of DM(P-nonlinear=0.395).

Conclusion

HRR is associated with the risk of DM, and higher HRR levels are protective against the development of diabetes.

, authors=Yan TANG1, Jie HUI3, Wan-jia ZHANG1, Bin-quan TANG1, Fan XIAO2, Rong YU2, authorsList=Yan TANG, Jie HUI, Wan-jia ZHANG, Bin-quan TANG, Fan XIAO, 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=1324078387723116641, articleId=1324078382715117652, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=血红蛋白-红细胞分布宽度比与糖尿病患病的关系——基于NHANES数据库的横断面研究, 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

探讨血红蛋白-红细胞分布宽度比（hemoglobin-to-red blood cell distribution width ratio,HRR）与糖尿病患病之间的关联。

方法

选取2001—2020年美国国家健康与营养调查（National Health and Nutrition Examination Survey，NHANES）数据库的16 392例参与者作为研究对象。采用logistic回归、亚组分析、限制性立方样条图（restricted cubic splines，RCS）分析了HRR与DM之间的相关性。

结果

纳入的参与者总体HRR为（0.27±0.98），糖尿病患者HRR低于对照组（P<0.001）。Logistic分析结果表明，将HRR作为连续性变量进行分析，HRR每增加一个标准差，发生DM的风险降低11%，（OR=0.89，95% CI：0.84～0.95）。将HRR作为分类变量按四分位数进行计算，与低水平HRR（Q1）相比，最高第四分位数（Q4）在三个模型中均显示糖尿病患病风险显著降低（OR<1）。亚组分析显示，在多数亚组中，HRR升高均与糖尿病患病风险降低相关（多组P值<0.05）。剂量-反应关系结果显示，HRR与糖尿病患病风险呈线性负相关（P-nonlinear =0.395）。

结论

HRR与糖尿病患病风险相关，高水平HRR对糖尿病具有保护作用。

, authors=唐燕1, 惠杰3, 张万佳1, 唐彬荃1, 肖凡2, 喻嵘2, authorsList=唐燕, 惠杰, 张万佳, 唐彬荃, 肖凡, 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:
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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、种族、婚姻状况、教育程度、PIR、吸烟状况、饮酒状况、健康饮食状况、中等强度运动状况、高血压病史、总胆固醇、低密度脂蛋白、高密度脂蛋白、甘油三酯、丙氨酸氨基转移酶、天冬氨酸转氨酶、血肌酐以及尿酸。

, figureFileSmall=fmT/FipOdFvrrZFG+F6VJQ==, figureFileBig=jKNYjnks115eoBIYH5UY0Q==, tableContent=null), ArticleFig(id=1324078394085875858, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078382715117652, language=EN, label=Figure 3, caption=Subgroup analysis for the association of HRR with diabetes mellitus, figureFileSmall=xiEwAfio7FrRaiKFzsnOuQ==, figureFileBig=BaEIvWnKVXlZcn0WMBgbRw==, tableContent=null), ArticleFig(id=1324078394173956243, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078382715117652, language=CN, label=图3, caption=HRR与糖尿病关联的亚组分析

注：校正了年龄、性别、种族、婚姻状况、教育程度、PIR、吸烟状况、饮酒状况、健康饮食状况、中等强度运动状况、高血压病史、总胆固醇、低密度脂蛋白、高密度脂蛋白、甘油三酯、丙氨酸氨基转移酶、天冬氨酸转氨酶、血肌酐以及尿酸。

, figureFileSmall=xiEwAfio7FrRaiKFzsnOuQ==, figureFileBig=BaEIvWnKVXlZcn0WMBgbRw==, tableContent=null), ArticleFig(id=1324078394249453716, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078382715117652, language=EN, label=Table 1, caption=

Clinical characteristics of NHANES participants, 2001—2020 [（），n（%）]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群（n=16 392）非糖尿病组（n=13 199）糖尿病组（n=3 193）t/χ2值P值
年龄（岁）47.47±16.7845.41±16.3959.32±13.8536.923<0.001
性别6.0470.015
男8 011 (48.8)6 335 (48.4)1 676 (51.6)
女8 381 (51.2)6 864 (51.6)1 517 (48.4)
种族6.918<0.001
墨西哥裔美国人2 528 (7.8)1 960 (7.7)568 (8.9)
其他西班牙裔1 395 (4.9)1 082 (4.9)313 (5.4)
非西班牙裔白人7 556 (70.5)6 260 (71.2)1 296 (66.4)
非西班牙裔黑人3 372 (10.1)2 613 (9.6)759 (12.7)
其他种族1 541 (6.6)1 284 (6.6)257 (6.6)
婚姻状况0.1740.678
已婚或与伴侣同居9 992 (64.7)8 039 (64.6)1 953 (65.2)
其他6 400 (35.3)5 160 (35.4)1 240 (34.8)
教育程度62.676<0.001
高中以下3 744 (14.6)2 735 (13.6)1 009 (20.8)
高中或同等学历3 798 (23.5)2 986 (22.5)812 (29.3)
高中以上8 850 (61.9)7 478 (63.9)1 372 (49.9)
PIR类别23.607<0.001
低水平（<1）3 140 (12.6)2 479 (12.4)661 (13.7)
中等水平（1～2.99）6 900 (35.5)5 375 (34.2)1 525 (42.9)
高水平（≥3）6 352 (51.9)5 345 (53.4)1 007 (43.4)
吸烟状况9.7680.002
是7 493 (45.9)5 900 (45.2)1 593 (50.4)
否8 899 (54.1)7 299 (54.8)1 600 (49.6)
饮酒状况51.019<0.001
是12 356 (80.2)10 115 (81.4)2 241 (73.2)
否4 036 (19.8)3 084 (18.6)952 (26.8)
健康饮食状况2.0330.158
是7 167 (43.2)5 720 (42.9)1 447 (44.7)
否9 225 (56.8)7 479 (57.1)1 746 (55.3)
中等强度运动状况88.416<0.001
是7 214 (44.0)6 104 (51.7)1 110 (37.8)
否9 178 (56.0)7 095 (48.3)2 083 (62.2)
BMI(kg/m2)29.07±6.9028.40±6.5132.92±7.7620.455<0.001
BMI类别(kg/m2)219.049<0.001
正常体重 (<25)4 704 (29.8)4 255 (32.9)449 (12.3)
超重 (25～29.99)5 467 (33.3)4 541 (34.3)926 (27.4)
肥胖 (≥30)6 221 (36.9)4 403 (32.8)1 818 (60.3)
高血压443.047<0.001
是5 952 (32.4)3 896 (27.1)2 056 (62.8)
否10 440 (67.6)9 303 (72.9)1 137 (37.2)
总胆固醇(mg/dl*)192.49±40.65193.83±39.87184.77±44.09-7.284<0.001
低密度脂蛋白(mg/dl*)113.86±35.68115.28±34.86105.68±39.06-9.437<0.001
高密度脂蛋白(mg/dl*)54.55±16.1755.46±16.0749.34±15.77-14.377<0.001
甘油三酯（mg/dl*）119.48±70.73114.47±66.97148.24±83.7315.398<0.001
丙氨酸氨基转移酶(U/L)24.95±18.7124.57±18.9027.10±17.415.763<0.001
天冬氨酸转氨酶(U/L)24.68±16.9724.46±16.7525.89±18.113.6880.025
肌酐(mg/dl*)0.89±0.390.87±0.310.97±0.686.519<0.001
血尿素氮(mg/dl*)13.47±5.3413.05±4.7815.91±7.3417.018<0.001
尿酸(mg/dl*)5.46±1.385.39±1.355.83±1.5210.532<0.001
白蛋白(g/l)4.21±0.344.23±0.344.11±0.35-11.410<0.001
血钙(mg/dl*)9.36±0.359.36±0.359.37±0.380.5920.619
血磷(mg/dl*)3.64±0.543.64±0.543.66±0.571.1450.418
白细胞（1 000个细胞/μl）6.78±2.196.67±2.177.41±2.1712.612<0.001
血小板（1 000个细胞/μl）247.10±64.66247.99±63.25242.01±72.02-3.245<0.001
HRR0.27±0.980.31±0.970.02±1.03-11.152<0.001
), ArticleFig(id=1324078394371088533, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078382715117652, language=CN, label=表1, caption=

2001—2020年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=16 392）非糖尿病组（n=13 199）糖尿病组（n=3 193）t/χ2值P值
年龄（岁）47.47±16.7845.41±16.3959.32±13.8536.923<0.001
性别6.0470.015
男8 011 (48.8)6 335 (48.4)1 676 (51.6)
女8 381 (51.2)6 864 (51.6)1 517 (48.4)
种族6.918<0.001
墨西哥裔美国人2 528 (7.8)1 960 (7.7)568 (8.9)
其他西班牙裔1 395 (4.9)1 082 (4.9)313 (5.4)
非西班牙裔白人7 556 (70.5)6 260 (71.2)1 296 (66.4)
非西班牙裔黑人3 372 (10.1)2 613 (9.6)759 (12.7)
其他种族1 541 (6.6)1 284 (6.6)257 (6.6)
婚姻状况0.1740.678
已婚或与伴侣同居9 992 (64.7)8 039 (64.6)1 953 (65.2)
其他6 400 (35.3)5 160 (35.4)1 240 (34.8)
教育程度62.676<0.001
高中以下3 744 (14.6)2 735 (13.6)1 009 (20.8)
高中或同等学历3 798 (23.5)2 986 (22.5)812 (29.3)
高中以上8 850 (61.9)7 478 (63.9)1 372 (49.9)
PIR类别23.607<0.001
低水平（<1）3 140 (12.6)2 479 (12.4)661 (13.7)
中等水平（1～2.99）6 900 (35.5)5 375 (34.2)1 525 (42.9)
高水平（≥3）6 352 (51.9)5 345 (53.4)1 007 (43.4)
吸烟状况9.7680.002
是7 493 (45.9)5 900 (45.2)1 593 (50.4)
否8 899 (54.1)7 299 (54.8)1 600 (49.6)
饮酒状况51.019<0.001
是12 356 (80.2)10 115 (81.4)2 241 (73.2)
否4 036 (19.8)3 084 (18.6)952 (26.8)
健康饮食状况2.0330.158
是7 167 (43.2)5 720 (42.9)1 447 (44.7)
否9 225 (56.8)7 479 (57.1)1 746 (55.3)
中等强度运动状况88.416<0.001
是7 214 (44.0)6 104 (51.7)1 110 (37.8)
否9 178 (56.0)7 095 (48.3)2 083 (62.2)
BMI(kg/m2)29.07±6.9028.40±6.5132.92±7.7620.455<0.001
BMI类别(kg/m2)219.049<0.001
正常体重 (<25)4 704 (29.8)4 255 (32.9)449 (12.3)
超重 (25～29.99)5 467 (33.3)4 541 (34.3)926 (27.4)
肥胖 (≥30)6 221 (36.9)4 403 (32.8)1 818 (60.3)
高血压443.047<0.001
是5 952 (32.4)3 896 (27.1)2 056 (62.8)
否10 440 (67.6)9 303 (72.9)1 137 (37.2)
总胆固醇(mg/dl*)192.49±40.65193.83±39.87184.77±44.09-7.284<0.001
低密度脂蛋白(mg/dl*)113.86±35.68115.28±34.86105.68±39.06-9.437<0.001
高密度脂蛋白(mg/dl*)54.55±16.1755.46±16.0749.34±15.77-14.377<0.001
甘油三酯（mg/dl*）119.48±70.73114.47±66.97148.24±83.7315.398<0.001
丙氨酸氨基转移酶(U/L)24.95±18.7124.57±18.9027.10±17.415.763<0.001
天冬氨酸转氨酶(U/L)24.68±16.9724.46±16.7525.89±18.113.6880.025
肌酐(mg/dl*)0.89±0.390.87±0.310.97±0.686.519<0.001
血尿素氮(mg/dl*)13.47±5.3413.05±4.7815.91±7.3417.018<0.001
尿酸(mg/dl*)5.46±1.385.39±1.355.83±1.5210.532<0.001
白蛋白(g/l)4.21±0.344.23±0.344.11±0.35-11.410<0.001
血钙(mg/dl*)9.36±0.359.36±0.359.37±0.380.5920.619
血磷(mg/dl*)3.64±0.543.64±0.543.66±0.571.1450.418
白细胞（1 000个细胞/μl）6.78±2.196.67±2.177.41±2.1712.612<0.001
血小板（1 000个细胞/μl）247.10±64.66247.99±63.25242.01±72.02-3.245<0.001
HRR0.27±0.980.31±0.970.02±1.03-11.152<0.001
), ArticleFig(id=1324078394467557526, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078382715117652, language=EN, label=Table 2, caption=

Logistic regression analysis of the association between HRR and diabetes mellitus

, figureFileSmall=null, figureFileBig=null, tableContent=
HRR模型 1模型 2模型 3
OR（95%CI）P值OR（95%CI）P值OR（95%CI）P值
每增加1个标准差0.75(0.71～0.79)<0.0010.82(0.77～ 0.88)<0.0010.89(0.84～0.95)<0.001
Q1RefRefRef
Q20.74(0.58～0.75)<0.0010.72(0.63～0.83)<0.0010.87(0.76～1.00)0.051
Q30.58(0.50～0.67)<0.0010.70(0.59～0.83)<0.0010.85(0.71～1.03)0.094
Q40.44(0.38～0.51)<0.0010.59(0.49～0.71)<0.0010.65(0.53～0.79)<0.001
趋势P值<0.001<0.001<0.001
), ArticleFig(id=1324078394538860695, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1324078382715117652, language=CN, label=表2, caption=

HRR与糖尿病的逻辑回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
HRR模型 1模型 2模型 3
OR（95%CI）P值OR（95%CI）P值OR（95%CI）P值
每增加1个标准差0.75(0.71～0.79)<0.0010.82(0.77～ 0.88)<0.0010.89(0.84～0.95)<0.001
Q1RefRefRef
Q20.74(0.58～0.75)<0.0010.72(0.63～0.83)<0.0010.87(0.76～1.00)0.051
Q30.58(0.50～0.67)<0.0010.70(0.59～0.83)<0.0010.85(0.71～1.03)0.094
Q40.44(0.38～0.51)<0.0010.59(0.49～0.71)<0.0010.65(0.53～0.79)<0.001
趋势P值<0.001<0.001<0.001
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血红蛋白-红细胞分布宽度比与糖尿病患病的关系——基于NHANES数据库的横断面研究
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唐燕 1 , 惠杰 3 , 张万佳 1 , 唐彬荃 1 , 肖凡 2 , 喻嵘 2
现代预防医学 | 流行病与统计方法 2026,53(1): 7-12
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现代预防医学 |流行病与统计方法 2026 , 53 (1) : 7 -12
血红蛋白-红细胞分布宽度比与糖尿病患病的关系——基于NHANES数据库的横断面研究
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唐燕1, 惠杰3, 张万佳1, 唐彬荃1, 肖凡2, 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

Hemoglobin-to-red cell distribution width ratio and diabetes mellitus:a cross-sectional analysis of NHANES database
Yan TANG1, Jie HUI3, Wan-jia ZHANG1, Bin-quan TANG1, Fan XIAO2, Rong YU2
Affiliations
  • The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, Hunan 410007, China
出版时间: 2026-01-10 doi: 10.20043/j.cnki.MPM.202507233
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摘要
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目的

探讨血红蛋白-红细胞分布宽度比（hemoglobin-to-red blood cell distribution width ratio,HRR）与糖尿病患病之间的关联。

方法

选取2001—2020年美国国家健康与营养调查（National Health and Nutrition Examination Survey，NHANES）数据库的16 392例参与者作为研究对象。采用logistic回归、亚组分析、限制性立方样条图（restricted cubic splines，RCS）分析了HRR与DM之间的相关性。

结果

纳入的参与者总体HRR为（0.27±0.98），糖尿病患者HRR低于对照组（P<0.001）。Logistic分析结果表明，将HRR作为连续性变量进行分析，HRR每增加一个标准差，发生DM的风险降低11%，（OR=0.89，95% CI：0.84～0.95）。将HRR作为分类变量按四分位数进行计算，与低水平HRR（Q1）相比，最高第四分位数（Q4）在三个模型中均显示糖尿病患病风险显著降低（OR<1）。亚组分析显示，在多数亚组中，HRR升高均与糖尿病患病风险降低相关（多组P值<0.05）。剂量-反应关系结果显示，HRR与糖尿病患病风险呈线性负相关（P-nonlinear =0.395）。

结论

HRR与糖尿病患病风险相关，高水平HRR对糖尿病具有保护作用。

血红蛋白-红细胞分布宽度比  /  糖尿病  /  NHANES
Objective

This study aims to explore the association between the hemoglobin-to-red blood cell distribution width ratio (HRR) and the risk of diabetes mellitus (DM).

Methods

A total of 16 392 participants from the 2001—2020 National Health and Nutrition Examination Survey(NHANES) database were selected for this study. Logistic regression, subgroup analysis, and restricted cubic splin (RCS) analysis were applied to investigate the relationship between HRR and DM.

Results

The mean HRR among the included participants was 0.27±0.98, with diabetic patients showing significantly lower HRR compared to the control group (P<0.001). Logistic regression analysis revealed that when HRR was modeled as a continuous variable, for each standard deviation increase in HRR, the risk of DM decreased by 11% (OR=0.89, 95% CI: 0.84-0.95). When HRR was treated as a categorical variable based on quartiles, the highest fourth quartile(Q4) consistently showed a significant reduction in DM risk compared to the lowest quartile (Q1) across all three models (OR<1). Subgroup analysis demonstrated that increased HRR was associated with a reduced risk of DM in most subgroups, with most P-values<0.05. The dose-response analysis indicated a linear negative correlation between HRR and the risk of DM(P-nonlinear=0.395).

Conclusion

HRR is associated with the risk of DM, and higher HRR levels are protective against the development of diabetes.

Hemoglobin-to-red cell distribution width ratio  /  Diabetes mellitus  /  NHANES
唐燕, 惠杰, 张万佳, 唐彬荃, 肖凡, 喻嵘. 血红蛋白-红细胞分布宽度比与糖尿病患病的关系——基于NHANES数据库的横断面研究. 现代预防医学, 2026 , 53 (1) : 7 -12 . DOI: 10.20043/j.cnki.MPM.202507233
Yan TANG, Jie HUI, Wan-jia ZHANG, Bin-quan TANG, Fan XIAO, Rong YU. Hemoglobin-to-red cell distribution width ratio and diabetes mellitus:a cross-sectional analysis of NHANES database[J]. Modern Preventive Medicine, 2026 , 53 (1) : 7 -12 . DOI: 10.20043/j.cnki.MPM.202507233
正文
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糖尿病是一种以血糖持续升高为主要特征的慢性代谢性疾病，可导致多个器官的严重损害，引发诸如心血管疾病、肾脏病变、神经病变等一系列并发症[1]。据国际糖尿病联盟统计显示，全球已有5.4亿成年人患糖尿病，预计到2045年，这一数字将达到7.8亿[2]。与非糖尿病患者相比，糖尿病患者的全因死亡率持续升高，已然成为公共卫生领域亟待应对的重要挑战[3]。
在糖尿病复杂的发病机制中，慢性低度炎症扮演着核心角色，其在加剧胰岛素抵抗的同时，也损害胰岛素的分泌功能[4-5]。糖尿病患者的炎症状态已被证实与红细胞分布宽度（red blood cell distribution width,RDW）的升高密切相关[6]。RDW作为一项常规血液学指标，其增高反映了造血功能障碍或红细胞存活异常，并与多种疾病预后及全因死亡率相关[7]。在此背景下，血红蛋白与红细胞分布宽度比（hemoglobin-to-red blood cell distribution width ratio,HRR）作为一个由血红蛋白与RDW构成的复合指标，近年来受到了越来越多关注[8]。研究显示，HRR在评估心脑血管疾病预后方面，优于单一的血液学参数[9-10]，并且与心力衰竭、慢性肾病及多种恶性肿瘤等多种慢性疾病的发生发展密切相关[11-13]。这得益于其能够独特地整合贫血与炎症这两大病理过程，因此HRR被视为一种颇具潜力的慢性炎症性疾病新型生物标志物。
尽管 HRR与众多疾病相关，但 HRR与糖尿病之间的临床关系仍不明确。因此，探究 HRR在糖尿病中的作用具有重要意义。本研究利用2001—2020年NHANES数据库的统计数据分析HRR和糖尿病之间的相关性，旨在为糖尿病的早期预警、风险分层以及治疗策略提供新的流行病学依据与思路。
1　对象与方法
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1.1　数据来源
本研究数据来源于美国国家健康与营养调查（National Health and Nutrition Examination Survey，NHANES）数据库。自1999年以来，NHANES每年对约5 000名代表性样本的美国居民进行访谈，采用分层、多阶段的概率抽样设计，确保样本具有广泛的代表性和统计学可靠性。该调查每两年收集一次数据，涉及健康状况、疾病风险和营养摄入等多个方面。调查遵循伦理标准，所有参与者均提供书面知情同意，确保数据的合规性[14]。详细的调查设计信息可参见NHANES官方网站(https://www.cdc.gov/nchs/hanes/)。本研究采用的是2001—2020年的9个不同时期的数据，排除标准：（1）20岁以下的个人;（2）缺失糖尿病诊断数据;（3）缺失HRR数据;（4）缺失纳入的协变量数据。最终16 392名对象被纳入最终分析。参与者选择的流程图见图1。
1.2　暴露和结局变量
HRR在本研究中被确定为暴露变量[10]。HRR是一个复合炎症生物标志物，由血红蛋白和RDW组成，是血红蛋白（以g/dl为单位）除以RDW。本研究中，HRR被视为一个连续变量和分为四分位数两种情况。
糖尿病根据以下标准定义：（1）空腹血糖水平≥7 mmol/L；（2）糖化血红蛋白（glycated hemoglobin，HbA1c）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糖尿病。当以上数值缺失或未达到糖尿病诊断标准时，自报糖尿病相关信息：（1）自我报告的诊断；（2）使用胰岛素；（3）使用降糖药物；满足其中任意一项满足也可以被定义为患有糖尿病[15]。
1.3　协变量
在NHANES调查中，所有协变量均按照统一的访谈、体检和实验室操作手册获取。包括：年龄、性别（男性或女性）和种族（墨西哥裔美国人、其他西班牙裔、非西班牙裔白人、非西班牙裔黑人或其他）、教育程度（低于高中、高中或同等学历、高于高中）、家庭收入贫困比（poverty income ratio,PIR）（<1.00、1.00～2.99、≥3.00）、婚姻状况（已婚或与伴侣同居，其他）、吸烟状况（一生累积吸≥100支香烟者判定为吸烟者）、饮酒状况（饮酒者被定义为过去12个月内摄入≥12杯任何酒精饮料）、健康饮食状况[健康饮食指数-2015（HEI-2015）来评估饮食质量，平均HEI分数等于或高于第60个百分位数的参与者被认为饮食健康]、中等强度的运动（是、否）、身体质量指数（body mass index，BMI）（分为正常体重、超重与肥胖）；高血压病史以及总胆固醇、低密度脂蛋白、高密度脂蛋白、甘油三酯、丙氨酸氨基转移酶、天冬氨酸转氨酶、血肌酐、血尿素氮、尿酸、白蛋白、血钙、血磷、白细胞计数、血小板计数等实验室指标。
1.4　统计方法
采用R 4.4.2进行分析。连续变量以加权均值和标准差表示，分类变量以加权比例报告。两组比较采用双尾Wilcoxon秩和检验，多组比较使用加权χ2检验。应用逻辑回归评估HRR和糖尿病之间的关联，建立三个统计模型：模型1未校正；模型2校正年龄、性别、种族、婚姻状况、教育程度以及PIR；模型3校正年龄、性别、种族、婚姻状况、教育程度、PIR、吸烟状况、饮酒状况、健康饮食状况、中等强度运动状况、高血压病史、总胆固醇、低密度脂蛋白、高密度脂蛋白、甘油三酯、丙氨酸氨基转移酶、天冬氨酸转氨酶、血肌酐以及尿酸。进行了年龄、性别、种族、婚姻状况、教育水平、PIR、BMI、吸烟和饮酒情况等因素的分层和交互作用分析。在亚组分析中，采用t检验（连续变量）或加权χ2检验（分类变量）。为了进一步评估HRR与糖尿病患病率之间的非线性关系，采用了限制立方样条（restricted cubic splines，RCS）方法。趋势检验评估HRR各分位数（Q1，Q2，Q3，Q4）之间的糖尿病患病率差异。所有统计结果均按照统计显著性进行报告，检验水准α=0.05。
2　结果
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2.1　调查对象的基本特征
本研究共纳入16 392名受试者，其中男性占49%，女性占51%。共有3 193名参与者患有糖尿病。与无糖尿病者相比，糖尿病患者具有以下特征：整体年龄偏大，男性占比较高；种族分布中墨西哥裔美国人、其他西班牙裔及非西班牙裔黑人的比例略高；同时，多为高中及以下学历、中低等家庭收入水平（PIR<3）、有吸烟史、高血压病史，较少进行中等强度活动（所有P<0.05）。在体重方面，糖尿病组的BMI显著较高，大多可划分为肥胖。在临床指标方面，糖尿病组的个体表现出甘油三酯、丙氨酸氨基转移酶、天冬氨酸转氨酶、肌酐、血尿素氮、尿酸、白细胞计数等水平的升高以及总胆固醇、低密度脂蛋白、高密度脂蛋白、白蛋白、血小板计数的降低（所有P<0.05）。见表1。
2.2　HRR与糖尿病之间的关系
Logistic回归分析结果显示，当HRR为连续变量时，在未调整混杂因素的模型1中，HRR每增加一个标准差，糖尿病患病的风险就降低25%。在进一步调整混杂变量的模型2和模型3中，这一关联仍然显著，OR分别为0.82和0.89（P<0.001）。见表2。
将HRR水平进行四分位分组，与HRR的最低四分位数（Q1）相比，最高第四分位数（Q4）在三个模型中均显示糖尿病风险显著降低（OR<1）。此外，趋势性检验结果显示，随着HRR水平的升高，糖尿病患病风险呈逐渐下降的线性趋势（所有趋势P<0.001）。值得注意的是，在完全调整的模型3中，Q2和Q3组的风险降低未达到统计学显著性（P=0.051和P=0.094），但整体趋势依然显著。见表2。
RCS分析结果表明，HRR与糖尿病之间存在线性关联（P-overall<0.001），无明显非线性关联（P-nonlinear=0.395）。当HRR降低时，糖尿病患病率增加。见图2。
2.3　亚组分析
按年龄、性别、种族、婚姻状况、教育程度、PIR、吸烟和饮酒状况以及BMI分类进行亚组分析。在多数亚组中，HRR升高均与糖尿病患病风险降低相关（多组P值<0.05），结果方向一致，提示该关联具有较好的稳健性。此外，HRR与糖尿病的关联在婚姻状况（P=0.003）中存在交互作用，提示婚姻状况这个社会人口学因素可能在HRR作用机制中起调节作用。见图3。
3　讨论
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本研究共纳入了16 392名受试者。研究结果表明: HRR与糖尿病患病率之间存在线性负相关关系，表现为HRR降低时，糖尿病患病率增加，提示HRR可能是糖尿病患病风险的潜在保护性标志物。
糖尿病已成为全球最为严峻的公共卫生问题之一，影响着数百万人的健康。根据世界卫生组织的数据，全球糖尿病患病率逐年上升，特别是在中低收入国家，糖尿病已成为导致死亡和残疾的主要原因之一[16]。除了对健康的直接影响外，糖尿病还带来了巨大的经济负担，与糖尿病相关的医疗费用占许多国家公共卫生预算的显著比例。
目前，糖尿病的诊断和管理主要依赖于空腹血糖和HbA1c等指标[17]。然而，这些标志物并未完全反映糖尿病的复杂病理生理机制，尤其是炎症的影响。为弥补这一局限，研究焦点已逐渐转向能综合反映炎症状态的新型复合指标。例如全身免疫炎症指数、中性粒细胞百分比与白蛋白比值，以及中性粒细胞与淋巴细胞比值等，均已被证实与糖尿病及其预后密切相关[18-20]。在此类新兴指标中，HRR因其独特的病理生理整合能力而备受关注。多项基于NHANES数据库的研究表明，较高的HRR水平通过其显著的抗炎与保护效应，对患病风险起到预测作用。具体而言，HRR的升高标志着炎症水平受控，能抑制炎症细胞因子对视网膜血管内皮的直接损害，保护微循环功能，降低了糖尿病视网膜病变的风险[21]；较高的 HRR可能反映较低的全身炎症负荷和较大的供氧能力，从而降低哮喘存在的可能性[22]；反之，HRR降低时，促炎细胞因子会破坏血脑屏障完整性并促进神经炎症，从而加速认知障碍[23]。这些证据共同提示，HRR是一个连接炎症以及糖尿病的有力生物标志物。
较高的 HRR在糖尿病发病机制中的保护作用可能涉及多种生物学机制。红细胞分布宽度（RDW）的升高通常与炎症密切相关，糖尿病患者的慢性低度炎症可能会通过影响铁代谢和骨髓功能，抑制促红细胞生成素诱导的红细胞成熟，从而导致未成熟的红细胞过早进入外周血，扰乱了红细胞的正常清除过程，最终引发RDW的升高[24]。在一项NHANES研究中，RDW最高五分位组的糖尿病患病率明显高于最低五分位组，这一关联在整个研究人群（11.0%vs.7.0%，OR= 1.55；95% CI：1.30～1.85）以及45岁及以上的患者中（13.6%vs.7.7%，OR=1.88；95% CI：1.50～2.37）依然显著[25]。血红蛋白浓度的降低与贫血密切相关。研究发现，糖尿病患者的贫血患病率高达35.45%[26]，故探讨HRR与糖尿病的关系具有一定的理论依据。
本研究的优势在于采用了具有全国代表性的美国成年人样本数据，模型中充分调整了社会人口学变量、实验室参数等多种混杂因素，从而提高了结论的稳健性。本研究结果为将HRR作为糖尿病的早期识别提供了理论依据和数据支持。本研究亦存在一定局限性。一是，由于研究采用横断面设计，难以推断HRR与糖尿病患病之间的因果关系；二是，由于数据基于自报和一次性实验测量，可能存在信息偏倚或测量误差。此外，尽管已纳入多个协变量以降低偏倚影响，但仍无法完全排除某些潜在混杂因素对结果的影响。
综上所述，HRR与糖尿病患病风险存在关联。因此，定期监测HRR值有望为糖尿病的早期干预与预后管理提供新思路。
基金
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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)
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2026年第53卷第1期
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doi: 10.20043/j.cnki.MPM.202507233
  • 接收时间：2025-07-13
  • 首发时间：2026-11-02
  • 出版时间：2026-01-10
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  • 收稿日期：2025-07-13
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)
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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喻嵘，E-mail:
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https://castjournals.cast.org.cn/joweb/xdyfyx/CN/10.20043/j.cnki.MPM.202507233
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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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