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Article(id=1240722571553984704, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240722566957027366, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202504437, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1745510400000, receivedDateStr=2025-04-25, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773740912568, onlineDateStr=2026-03-17, pubDate=1760025600000, pubDateStr=2025-10-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773740912568, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773740912568, creator=13701087609, updateTime=1773740912568, updator=13701087609, issue=Issue{id=1240722566957027366, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='19', pageStart='3457', pageEnd='3648', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=0, createTime=1773740911472, creator=13701087609, updateTime=1773740981732, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240722861736906836, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240722566957027366, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240722861736906837, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240722566957027366, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3509, endPage=3514, ext={EN=ArticleExt(id=1240722571855974614, articleId=1240722571553984704, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Relationship between body roundness index and depression risk among individuals with hyperlipidemia, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=

Objective To examine the relationship between body roundness index (BRI) and depression risk in individuals with hyperlipidemia. Methods Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2005—2018, including 20 492 adults with hyperlipidemia. Multivariable logistic regression and restricted cubic spline analyses were used to analyze the association between BRI and depressive status. Results Multivariable analysis revealed a significant U-shaped relationship between BRI and depression risk (P=0.002), with an inflection point at 3.15. For BRI<3.15, each unit increase in BRI was associated with a 33% decrease in depression risk (OR=0.67, 95% CI: 0.50-0.88, P=0.004 3). For BRI≥3.15, each unit increase in BRI was associated with a 7% increase in depression risk (OR=1.07, 95% CI: 1.04-1.09, P<0.000 1). In tertile analysis, the highest BRI tertile showed a 30% increased risk of depression compared to the lowest tertile(OR=1.30, 95% CI: 1.13-1.49, P=0.000 2). Conclusion There is a U-shaped relationship between BRI and depression risk in individuals with hyperlipidemia, suggesting that both excessively low and high BRI values may increase the risk of depression.Large prospective cohort studies are needed to validate these findings.

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目的 探讨高脂血症人群身体圆度指数（body roundness index，BRI）与抑郁风险的关系。方法 利用2005—2018年美国国家营养与健康调查数据库数据，纳入20 492名高脂血症成年人。采用多因素logistic回归和限制性立方样条分析BRI与抑郁状态的关联。结果 多因素分析显示BRI与抑郁风险存在显著U型关系(P=0.002)，转折点为3.15。当BRI<3.15时，BRI每增加1单位，抑郁风险降低33%(OR=0.67, 95%CI: 0.50～0.88, P=0.004 3)；当BRI ≥ 3.15时，BRI每增加1单位，抑郁风险增加7%(OR=1.07, 95%CI: 1.04～1.09, P<0.000 1)。BRI三分位分组中，高BRI组较低BRI组抑郁风险增加30%(OR=1.30, 95%CI: 1.13～1.49, P=0.000 2)。结论 高脂血症人群中BRI与抑郁风险呈U型关系，BRI过低或过高均可能增加抑郁风险,未来仍需大规模前瞻性队列验证。

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周立春，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=la7jG2d13Se2tvgPUIUk/g==, magXml=aqlFJ4LHI1nhJDnU0Zeepw==, pdfUrl=null, pdf=UEPphaRh5PqrHXI5MvPtlA==, pdfFileSize=666621, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=RvfoZcrDkAik0kYiNScq6w==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=sYUXDMbQdRRPyZ2f9tJ9DQ==, mapNumber=null, authorCompany=null, fund=null, authors=

李见（1985—），女，博士，主治医师，研究方向：精神心理疾病

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李见（1985—），女，博士，主治医师，研究方向：精神心理疾病

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李见（1985—），女，博士，主治医师，研究方向：精神心理疾病

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journalId=1227665162245664772, articleId=1240722571553984704, language=CN, orderNo=4, keyword=横断面研究), Keyword(id=1240933509418775331, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=CN, orderNo=5, keyword=NHANES)], refs=[Reference(id=1240933510840644461, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, doi=null, pmid=null, pmcid=null, year=2023, volume=37, issue=9, pageStart=1731, pageEnd=1738, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=Mrowietz U, Sümbül M, Depression GS, journalName=JEADV, refType=null, unstructuredReference=Mrowietz U, Sümbül M, Depression GS. 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Front Cardiovasc Med,2022, 9: 879726., articleTitle=Electronic cigarette use and the risk of cardiovascular diseases, refAbstract=null)], funds=[Fund(id=1240933510630929252, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, awardId=22557760K, language=CN, fundingSource=河北省科技厅科研基金(22557760K), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1240933506570842757, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, xref=1., ext=[AuthorCompanyExt(id=1240933506575037061, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, companyId=1240933506570842757, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100043, China), AuthorCompanyExt(id=1240933506587619975, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, companyId=1240933506570842757, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.首都医科大学医学附属北京朝阳医院神经内科，北京 100043)]), AuthorCompany(id=1240933506684088971, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, xref=2., ext=[AuthorCompanyExt(id=1240933506700866187, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, companyId=1240933506684088971, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.河北北方学院附属第一医院神经内科)]), AuthorCompany(id=1240933506822501017, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, xref=3., ext=[AuthorCompanyExt(id=1240933506830889627, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, companyId=1240933506822501017, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.昆明市第三人民医院公共检验科/云南省传染病临床医学中心)])], figs=[ArticleFig(id=1240933509666239281, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=EN, label=Figure 1, caption=Flowchart of screening the study population, figureFileSmall=tLPapm0U+l3Jyws5t5UKVw==, figureFileBig=d6vM6ol7ki26duZ4OMJ92w==, tableContent=null), ArticleFig(id=1240933509745931063, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=CN, label=图1, caption=研究人群筛选流程图, figureFileSmall=tLPapm0U+l3Jyws5t5UKVw==, figureFileBig=d6vM6ol7ki26duZ4OMJ92w==, tableContent=null), ArticleFig(id=1240933509875954493, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=EN, label=Figure 2, caption=Relationship between BRI and risk of depression among patients with hyperlipidemia as demonstrated by smoothed curve fitting analysis, figureFileSmall=hGfQhJg/rTGiT9TQpgACEA==, figureFileBig=TUb67alRGYLgEp56xOaJTQ==, tableContent=null), ArticleFig(id=1240933509997589314, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=CN, label=图2, caption=平滑曲线拟合显示的BRI与高脂血症患者抑郁发生风险的关系, figureFileSmall=hGfQhJg/rTGiT9TQpgACEA==, figureFileBig=TUb67alRGYLgEp56xOaJTQ==, tableContent=null), ArticleFig(id=1240933510106641225, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=EN, label=Table 1, caption=

Baseline characteristics of individuals with hyperlipidemia stratified by BRI tertiles ［（）， n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群Tertiles1(1.17～4.64)Tertiles2(4.64～6.37)Tertiles3(6.37～17.86)统计量P值
（n=20 492）（n=6 834）（n=6 833）（n=6 825）
年龄（岁）49.96±17.2845.37±17.3151.92±16.7352.60±16.8896.398<0.001
性别54.741<0.001
男性10 582 (51.64)3 983 (58.28)3 868 (56.61)2 731 (40.01)
女性9 910 (48.36)2 851 (41.72)2 965 (43.39)4 094 (59.99)
种族613.523<0.001
墨西哥裔美国人3 637 (17.75)840 (12.29)1 404 (20.55)1 393 (20.41)
其他西班牙裔2 128 (10.38)583 (8.53)807 (11.81)738 (10.81)
非西班牙裔12 593 (61.45)4 299 (62.91)3 973 (58.14)4 321 (63.31)
其他2 134 (10.41)1 112 (16.27)649 (9.50)373 (5.47)
教育程度14.648<0.001
高中以下5 033 (24.56)1 276 (18.67)1 817 (26.59)1 940 (28.42)
高中4 674 (22.81)1 385 (20.27)1 594 (23.33)1 695 (24.84)
大学及以上10 128 (49.42)3 781 (55.33)3 301 (48.31)3 046 (44.63)
缺失657 (3.21)392 (5.74)121 (1.77)144 (2.11)
婚姻7.362<0.001
已婚/同居12 534 (61.17)4 032 (59.00)4 505 (65.93)3 997 (58.56)
丧偶/离婚/分居/未婚7 470 (36.45)2 511 (36.74)2 243 (32.83)2 716 (39.79)
缺失488 (2.38)291 (4.26)85 (1.24)112 (1.64)
PIR8.236<0.001
<1.35 921 (28.89)1 757 (25.71)1 887 (27.62)2 277 (33.36)
1.3～3.57 095 (34.62)2 221 (32.50)2 425 (35.49)2 449 (35.88)
>3.55 804 (28.32)2 309 (33.79)1 957 (28.64)1 538 (22.53)
缺失1 672 (8.16)547 (8.00)564 (8.25)561 (8.22)
饮酒情况18.478<0.001
非饮酒者5 003 (24.41)1 418 (20.75)1 582 (23.15)2 003 (29.35)
饮酒者12 531 (61.15)4 453 (65.16)4 327 (63.33)3 751 (54.96)
缺失2 958 (14.43)963 (14.09)924 (13.52)1 071 (15.69)
体力活动8.529<0.001
积极活动10 221 (49.88)3 310 (48.43)3 322 (48.62)3 589 (52.59)
较少活动1 361 (6.64)452 (6.61)431 (6.31)478 (7.00)
无活动6 071 (29.63)2 041 (29.87)2 125 (31.10)1 905 (27.91)
缺失2 839 (13.85)1 031 (15.09)955 (13.98)853 (12.50)
吸烟9.156<0.001
从不10 712 (52.27)3 575 (52.31)3 528 (51.63)3 609 (52.88)
现在5 094 (24.86)1 345 (19.68)1 852 (27.10)1 897 (27.79)
以前4 266 (20.82)1 659 (24.28)1 380 (20.20)1 227 (17.98)
缺失420 (2.05)255 (3.73)73 (1.07)92 (1.35)
睡眠障碍7.891<0.001
否15 095 (73.66)5 382 (78.75)5 198 (76.07)4 515 (66.15)
是5 389 (26.30)1 451 (21.23)1 630 (23.85)2 308 (33.82)
缺失8 (0.04)1 (0.01)5 (0.07)2 (0.03)
心血管疾病14.947<0.001
否17 807 (86.90)6 079 (88.95)6 036 (88.34)5 692 (83.40)
是2 040 (9.96)371 (5.43)680 (9.95)989 (14.49)
缺失645 (3.15)384 (5.62)117 (1.71)144 (2.11)
高血压12.539<0.001
否12 897 (62.94)5 324 (77.90)4 261 (62.36)3 312 (48.53)
是7 583 (37.00)1 508 (22.07)2 566 (37.55)3 509 (51.41)
缺失12 (0.06)2 (0.03)6 (0.09)4 (0.06)
糖尿病13.277<0.001
否16 825 (82.11)6 363 (93.11)5 732 (83.89)4 730 (69.30)
是3 667(17.89)471(6.89)1 101(16.11)2 095(30.70)
), ArticleFig(id=1240933510219887437, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=CN, label=表1, caption=

按BRI三分位数分层的高脂血症人群基线特征［（），n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群Tertiles1(1.17～4.64)Tertiles2(4.64～6.37)Tertiles3(6.37～17.86)统计量P值
（n=20 492）（n=6 834）（n=6 833）（n=6 825）
年龄（岁）49.96±17.2845.37±17.3151.92±16.7352.60±16.8896.398<0.001
性别54.741<0.001
男性10 582 (51.64)3 983 (58.28)3 868 (56.61)2 731 (40.01)
女性9 910 (48.36)2 851 (41.72)2 965 (43.39)4 094 (59.99)
种族613.523<0.001
墨西哥裔美国人3 637 (17.75)840 (12.29)1 404 (20.55)1 393 (20.41)
其他西班牙裔2 128 (10.38)583 (8.53)807 (11.81)738 (10.81)
非西班牙裔12 593 (61.45)4 299 (62.91)3 973 (58.14)4 321 (63.31)
其他2 134 (10.41)1 112 (16.27)649 (9.50)373 (5.47)
教育程度14.648<0.001
高中以下5 033 (24.56)1 276 (18.67)1 817 (26.59)1 940 (28.42)
高中4 674 (22.81)1 385 (20.27)1 594 (23.33)1 695 (24.84)
大学及以上10 128 (49.42)3 781 (55.33)3 301 (48.31)3 046 (44.63)
缺失657 (3.21)392 (5.74)121 (1.77)144 (2.11)
婚姻7.362<0.001
已婚/同居12 534 (61.17)4 032 (59.00)4 505 (65.93)3 997 (58.56)
丧偶/离婚/分居/未婚7 470 (36.45)2 511 (36.74)2 243 (32.83)2 716 (39.79)
缺失488 (2.38)291 (4.26)85 (1.24)112 (1.64)
PIR8.236<0.001
<1.35 921 (28.89)1 757 (25.71)1 887 (27.62)2 277 (33.36)
1.3～3.57 095 (34.62)2 221 (32.50)2 425 (35.49)2 449 (35.88)
>3.55 804 (28.32)2 309 (33.79)1 957 (28.64)1 538 (22.53)
缺失1 672 (8.16)547 (8.00)564 (8.25)561 (8.22)
饮酒情况18.478<0.001
非饮酒者5 003 (24.41)1 418 (20.75)1 582 (23.15)2 003 (29.35)
饮酒者12 531 (61.15)4 453 (65.16)4 327 (63.33)3 751 (54.96)
缺失2 958 (14.43)963 (14.09)924 (13.52)1 071 (15.69)
体力活动8.529<0.001
积极活动10 221 (49.88)3 310 (48.43)3 322 (48.62)3 589 (52.59)
较少活动1 361 (6.64)452 (6.61)431 (6.31)478 (7.00)
无活动6 071 (29.63)2 041 (29.87)2 125 (31.10)1 905 (27.91)
缺失2 839 (13.85)1 031 (15.09)955 (13.98)853 (12.50)
吸烟9.156<0.001
从不10 712 (52.27)3 575 (52.31)3 528 (51.63)3 609 (52.88)
现在5 094 (24.86)1 345 (19.68)1 852 (27.10)1 897 (27.79)
以前4 266 (20.82)1 659 (24.28)1 380 (20.20)1 227 (17.98)
缺失420 (2.05)255 (3.73)73 (1.07)92 (1.35)
睡眠障碍7.891<0.001
否15 095 (73.66)5 382 (78.75)5 198 (76.07)4 515 (66.15)
是5 389 (26.30)1 451 (21.23)1 630 (23.85)2 308 (33.82)
缺失8 (0.04)1 (0.01)5 (0.07)2 (0.03)
心血管疾病14.947<0.001
否17 807 (86.90)6 079 (88.95)6 036 (88.34)5 692 (83.40)
是2 040 (9.96)371 (5.43)680 (9.95)989 (14.49)
缺失645 (3.15)384 (5.62)117 (1.71)144 (2.11)
高血压12.539<0.001
否12 897 (62.94)5 324 (77.90)4 261 (62.36)3 312 (48.53)
是7 583 (37.00)1 508 (22.07)2 566 (37.55)3 509 (51.41)
缺失12 (0.06)2 (0.03)6 (0.09)4 (0.06)
糖尿病13.277<0.001
否16 825 (82.11)6 363 (93.11)5 732 (83.89)4 730 (69.30)
是3 667(17.89)471(6.89)1 101(16.11)2 095(30.70)
), ArticleFig(id=1240933510345716563, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=EN, label=Table 2, caption=

Multivariable logistic regression results for the association between BRI and depression risk across different adjustment models in individuals with hyperlipidemia

, figureFileSmall=null, figureFileBig=null, tableContent=
变量非调整模型调整模型I调整模型II
OR（95%CI）P值OR（95%CI）P值OR（95%CI）P值
BRI1.15 (1.12～1.17)<0.000 11.05 (1.03～1.08)<0.000 11.05 (1.03～1.07)<0.000 1
BRI三分位数
Tertiles11.001.001.00
Tertiles21.24 (1.09～1.41)0.001 01.15 (1.00～1.32)0.049 61.13 (0.99～1.30)0.075 1
Tertiles32.01(1.78～2.26)<0.000 11.31(1.15～1.51)<0.000 11.30(1.13～1.49)0.000 2
), ArticleFig(id=1240933510429602650, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722571553984704, language=CN, label=表2, caption=

不同调整模型下高脂血症患者BRI与抑郁风险的多因素logistic回归分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量非调整模型调整模型I调整模型II
OR（95%CI）P值OR（95%CI）P值OR（95%CI）P值
BRI1.15 (1.12～1.17)<0.000 11.05 (1.03～1.08)<0.000 11.05 (1.03～1.07)<0.000 1
BRI三分位数
Tertiles11.001.001.00
Tertiles21.24 (1.09～1.41)0.001 01.15 (1.00～1.32)0.049 61.13 (0.99～1.30)0.075 1
Tertiles32.01(1.78～2.26)<0.000 11.31(1.15～1.51)<0.000 11.30(1.13～1.49)0.000 2
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高脂血症人群中身体圆度指数与抑郁风险关系的分析
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李见 1 , 王刚 2 , 李秋静 3 , 周立春 1
现代预防医学 | 流行病与统计方法 2025,52(19): 3509-3514
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现代预防医学 | 流行病与统计方法 2025, 52(19): 3509-3514
高脂血症人群中身体圆度指数与抑郁风险关系的分析
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李见1, 王刚2, 李秋静3, 周立春1
作者信息
  • 1.首都医科大学医学附属北京朝阳医院神经内科，北京 100043
  • 2.河北北方学院附属第一医院神经内科
  • 3.昆明市第三人民医院公共检验科/云南省传染病临床医学中心

    • 李见（1985—），女，博士，主治医师，研究方向：精神心理疾病

通讯作者:

周立春，E-mail:
Relationship between body roundness index and depression risk among individuals with hyperlipidemia
Jian LI1, Gang WANG2, Qiu-jing LI3, Li-chun ZHOU1
Affiliations
  • Department of Neurology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100043, China
出版时间: 2025-10-10 doi: 10.20043/j.cnki.MPM.202504437
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目的 探讨高脂血症人群身体圆度指数（body roundness index，BRI）与抑郁风险的关系。方法 利用2005—2018年美国国家营养与健康调查数据库数据，纳入20 492名高脂血症成年人。采用多因素logistic回归和限制性立方样条分析BRI与抑郁状态的关联。结果 多因素分析显示BRI与抑郁风险存在显著U型关系(P=0.002)，转折点为3.15。当BRI<3.15时，BRI每增加1单位，抑郁风险降低33%(OR=0.67, 95%CI: 0.50～0.88, P=0.004 3)；当BRI ≥ 3.15时，BRI每增加1单位，抑郁风险增加7%(OR=1.07, 95%CI: 1.04～1.09, P<0.000 1)。BRI三分位分组中，高BRI组较低BRI组抑郁风险增加30%(OR=1.30, 95%CI: 1.13～1.49, P=0.000 2)。结论 高脂血症人群中BRI与抑郁风险呈U型关系，BRI过低或过高均可能增加抑郁风险,未来仍需大规模前瞻性队列验证。

身体圆度指数  /  抑郁  /  高脂血症  /  横断面研究  /  NHANES

Objective To examine the relationship between body roundness index (BRI) and depression risk in individuals with hyperlipidemia. Methods Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2005—2018, including 20 492 adults with hyperlipidemia. Multivariable logistic regression and restricted cubic spline analyses were used to analyze the association between BRI and depressive status. Results Multivariable analysis revealed a significant U-shaped relationship between BRI and depression risk (P=0.002), with an inflection point at 3.15. For BRI<3.15, each unit increase in BRI was associated with a 33% decrease in depression risk (OR=0.67, 95% CI: 0.50-0.88, P=0.004 3). For BRI≥3.15, each unit increase in BRI was associated with a 7% increase in depression risk (OR=1.07, 95% CI: 1.04-1.09, P<0.000 1). In tertile analysis, the highest BRI tertile showed a 30% increased risk of depression compared to the lowest tertile(OR=1.30, 95% CI: 1.13-1.49, P=0.000 2). Conclusion There is a U-shaped relationship between BRI and depression risk in individuals with hyperlipidemia, suggesting that both excessively low and high BRI values may increase the risk of depression.Large prospective cohort studies are needed to validate these findings.

Body roundness index  /  Depression  /  Hyperlipidemia  /  Cross-sectional study  /  NHANES
李见, 王刚, 李秋静, 周立春. 高脂血症人群中身体圆度指数与抑郁风险关系的分析. 现代预防医学, 2025 , 52 (19) : 3509 -3514 . DOI: 10.20043/j.cnki.MPM.202504437
Jian LI, Gang WANG, Qiu-jing LI, Li-chun ZHOU. Relationship between body roundness index and depression risk among individuals with hyperlipidemia[J]. Modern Preventive Medicine, 2025 , 52 (19) : 3509 -3514 . DOI: 10.20043/j.cnki.MPM.202504437
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高脂血症是一种常见的代谢性疾病，全球患病率呈持续上升趋势。据最新研究显示，全球约有38.9%的成年人患有高脂血症[1-2]，中国成年人高脂血症患病率为40.4%，且地区发展水平、性别和年龄存在差异[1]。与此同时，抑郁症也已成为全球重要的公共卫生问题。世界卫生组织报告指出，全球约有2.8亿人患有抑郁症，占总人口的3.8%[3]。在中国，抑郁症的终生患病率达6.8%，12个月患病率为3.6%。高脂血症患者中抑郁症的患病率明显高于普通人群，据报道可达24.2%，这表明代谢紊乱与心理健康之间可能存在潜在联系[4]。身体圆度指数(body roundness index, BRI)是2013年由Thomas等人[5-6]提出的一种新型体型评估指标，基于身高和腰围数据计算，能更准确地反映人体脂肪分布状况，特别是腹部脂肪堆积情况。与传统的身体质量指数((body mass index,BMI)相比，BRI在预测代谢疾病风险方面表现出更高的敏感性和特异性[7-8]。目前关于高脂血症人群BRI与心理健康，尤其是抑郁风险之间关系的研究相对有限。本研究旨在利用美国国家健康与营养调查(National Health and Nutrition Examination Survey，NHANES)大型数据库，探讨高脂血症人群中BRI与抑郁风险之间的关系，为深入理解体脂分布与心理健康关系的病理生理机制提供依据。
1　材料与方法
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1.1　研究人群
本研究采用NHANES数据库2005—2018年的横断面数据，研究对象为20岁以上的高脂血症成年人群。高脂血症的诊断标准参照美国胆固醇教育计划（National Cholesterol Education Program, NCEP）第三次成人治疗专家组（ATP III）的定义[9]。共纳入20 492名符合条件的研究对象。纳入标准：（1）年龄大于20岁；（2）满足高脂血症诊断标准；（3）腰围和身高数据完整；（4）抑郁评估问卷无缺失。排除标准：（1）暴露或结局变量信息缺失；（2）妊娠或哺乳期妇女；（3）身体状况不适合测量身高体重者。研究入选流程图参见图1
1.2　变量测量
1.2.1　暴露变量
BRI其计算公式为[10]：
身高和腰围数据均在NHANES体检中心通过标准化方法测量，使用经校准的电子测量设备，由经过培训的专业人员执行[11]。
1.2.2　结局变量
抑郁状态通过患者健康问卷-9（PHQ-9）评估或自报既往抑郁症诊断确定。PHQ-9由9个条目组成，每个条目评分0～3分，总分范围0～27分，≥ 10分被定义为具有临床意义的抑郁症状[12-13]。此外，对于自报曾被医生诊断为抑郁症的受试者也被归类为抑郁。抑郁状态在数据库中以二分类变量形式记录（是/否）。
1.2.3　协变量
（1）人口学特征：年龄、性别、种族、受教育程度、婚姻状态；（2）社会经济因素：收入贫困比（poverty income ratio,PIR）；（3）生活方式因素：吸烟状态、饮酒习惯、体力活动水平；（4）健康状况：糖尿病、高血压、睡眠障碍。选择这些协变量基于既往文献证实其与抑郁及体重状态均相关，可能是潜在的混杂因素[14-15]。各变量采用标准化方法测量和分类，如吸烟状态分为从不吸烟、既往吸烟和目前吸烟；饮酒习惯分为不饮酒、轻/中度饮酒和重度饮酒；体力活动依据美国体力活动指南分为无活动、较少活动和积极活动三类。采用哑变量方法处理缺失值，即为每个存在缺失的变量创建一个指示变量，以捕捉缺失信息可能蕴含的重要特征[16]。
1.2.4　统计学分析
本研究使用易侕统计软件(V1.22.0)和R软件(4.1.0)进行数据分析。正态分布计量资料以（均数±标准差）表示，非正态分布以中位数（四分位数间距）表示；计数资料以例数（百分比）表示。分类变量比较采用χ2检验或Fisher确切概率法，连续变量比较采用方差分析或Kruskal-Wallis检验。研究对象根据BRI值分为三组（T1、T2、T3），T1组（最低三分位）为参照组。通过多因素logistic回归分析评估BRI与抑郁风险关联，计算比值比（odds ratio,OR）及95%置信区间（confidence indexval, 95%CI）。模型1为未调整模型；模型2调整年龄、性别和种族；模型3进一步调整婚姻状况、教育水平、家庭收入、体力活动、吸烟、饮酒、高血压、糖尿病、心血管疾病及睡眠障碍等混杂因素。使用限制性立方样条（restricted cubic splines，RCS）绘制BRI与抑郁风险log(OR)的剂量-反应曲线，并通过对数似然比检验评估其统计学意义。此外，采用阈值饱和效应分析确定潜在风险转折点，并通过分段logistic回归量化不同BRI值区间的关联强度，检验水准α=0.05。
2　结果
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2.1　研究对象的基线特征
本研究纳入20 492名高脂血症患者，按BRI三分位数分为三组：Tertiles1、Tertiles2和Tertiles3。三组之间在人口统计学特征和临床特点上均存在显著差异（均P<0.001）。随着BRI的升高，患者的平均年龄、男性比例、受教育程度、饮酒率、积极体力活动比例及吸烟率均有变化；而睡眠障碍、心血管疾病、高血压和糖尿病的患病率则显著增加。见表1。
2.2　BRI与抑郁风险的关联分析
为控制混杂因素，建立三个多因素逻辑回归模型。未调整模型中，BRI每增加1单位，抑郁风险增加15%（OR=1.15,95%CI: 1.12～1.17, P<0.000 1）。全面调整模型（模型II）中，风险增加5%（OR=1.05, 95%CI: 1.03～1.07, P<0.000 1）。按BRI三分位数分组分析：未调整模型中，中BRI组（T2）抑郁风险较低BRI组（T1）增加24%（OR=1.24, P=0.001 0），高BRI组（T3）增加101%（OR=2.01, P<0.000 1）。调整后，在模型I中中BRI组风险增加15%（OR=1.15, P=0.049 6），高BRI组增加31%（OR=1.31, P<0.000 1）；在模型II中，中BRI组差异不显著（OR=1.13, P=0.075 1），高BRI组风险显著增加30%（OR=1.30, P=0.000 2）。见表2。
2.3　BRI与抑郁风险的非线性关系分析
分段线性回归分析BRI与抑郁风险的关系显示U型非线性，见图2。阈值分析表明，BRI=3.15为转折点：当BRI<3.15时，每增加1个单位，抑郁风险降低33%（OR=0.67, 95%CI: 0.50～0.88, P=0.0043）；当BRI≥3.15时，风险增加7%（OR=1.07, 95%CI: 1.04～1.09, P<0.0001）。对数似然比检验确认了这一非线性关系。
3　讨论
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本研究探讨了高脂血症人群中BRI与抑郁风险的关系。结果表明，BRI与抑郁风险呈现显著的U型关系，过低或过高的BRI均与抑郁风险增加相关，而接近阈值的中等BRI水平则对应较低的抑郁风险，且这种非线性关联在多模型逐步调整多种潜在混杂因素后仍然稳健。
本研究发现与既往研究结果存在明显差异。Zhang等人[17]基于NHANES 2005—2018数据发现一般人群中BRI与抑郁呈正相关线性关系，动脉粥样硬化指数在此关联中发挥中介作用。而本研究聚焦高脂血症人群，首次揭示了BRI与抑郁的U型关系，高脂血症患者代表了一类基础脂质代谢已经异常的特殊人群，其体形与心理健康的关联模式可能与普通人群存在根本差异。在高脂血症患者中，即使是低BRI个体也存在脂质代谢异常，这与一般人群中的低BRI个体有本质区别。高脂血症患者体内异常的脂质分布和代谢可能通过特异性机制影响心理健康：一方面，异常脂质谱可直接影响神经细胞膜的组成和功能，干扰神经递质合成和信号传导[18]；另一方面，高脂血症药物治疗本身可能影响情绪调节[19]。此外，高脂血症患者体内存在特定的炎症表型和氧化应激模式，可能独立于体重影响神经系统功能，这解释了为何在高脂血症这一特定代谢背景下，BRI与抑郁的关联呈现出与一般人群不同的U型模式[20]。
作为评估中心性肥胖的新型指标，BRI通过结合腰围和身高，比传统体形指标如BMI更准确反映中心性肥胖状态，与代谢紊乱和心血管风险密切相关[21]。高脂血症是一种常见慢性代谢性疾病，全球患病率持续上升，与多种心脑血管疾病密切相关。同时，抑郁症是全球疾病负担的主要贡献因素，而高脂血症与抑郁的共病率显著高于普通人群[22]。探索这一特殊人群中体形指标与抑郁的关联，对理解和管理这类患者的综合健康风险至关重要。
在高脂血症患者，低BRI与抑郁风险增加可能涉及多种特异性机制。首先，虽然低BRI常伴随营养不良和能量摄入不足，导致体力与认知功能下降，但对高脂血症患者而言，情况更为复杂。即使BRI较低，这些患者体内脂质代谢仍然异常，在脂质代谢已紊乱的基础上，能量分配失衡可能特异性影响神经递质平衡和合成。研究表明，高脂血症患者即使在低体重状态下，其体内脂质分布和功能也与健康人群不同，可能更易导致神经系统功能紊乱[23]。此外，高脂血症合并低BRI可能反映疾病严重程度或药物治疗的影响。某些降脂药物可能影响能量代谢和体重，同时对情绪产生潜在影响[24]。值得注意的是，高脂血症患者中低BRI可能代表特殊亚型患者，其基因和代谢特征与典型患者不同，可能具有独特的心理健康风险谱[23]。另一方面，高脂血症患者中高BRI与抑郁的正相关关系也通过特定机制实现，且这些机制在脂质代谢异常背景下可能被强化[25]。脂肪组织作为活跃的内分泌器官分泌多种生物活性物质，如瘦素、脂联素和炎症因子等，在高脂血症患者中，这些物质的功能异常可能更为显著，通过影响下丘脑-垂体-肾上腺轴(hypothalamic-pituitary-adrenal axis，HPA)功能、神经递质代谢和神经可塑性等途径调节情绪[25]。多项研究表明，高脂血症患者的HPA轴功能异常与抑郁症状密切相关[26]。炎症反应是肥胖与抑郁之间的重要中介因素，而高脂血症患者往往处于慢性炎症状态，促炎因子水平升高可直接影响中枢神经系统功能[27]。肠道微生物组的改变通过肠-脑轴影响神经功能，高脂血症患者的肠道菌群失调可能加剧全身炎症反应，进一步增加抑郁风险[28-29]。此外，高脂血症直接影响神经细胞膜功能和神经递质代谢，高BRI高脂血症患者通常合并多种慢性疾病，如糖尿病、心血管疾病，这些疾病可通过血管内皮功能障碍和微血管损伤等机制，增强BRI与抑郁的关联[30]。
本研究具有以下优势：一是，基于美国大规模国民健康与营养调查数据，纳入20 492名高脂血症成年人，大样本量提高了统计效能和结果可靠性。二是，采用RCS和分段线性回归方法，探讨了BRI与抑郁风险的非线性关系，明确阈值，为临床实践提供具体参考值。
本研究存在若干局限性：首先，基于NHANES横断面数据，无法确定BRI与抑郁的因果关系，仅能提供关联性证据。其次，尽管调整了混杂因素，仍可能存在遗传易感性和早期生活事件等残余混杂。再次，抑郁状态评估依赖自报和PHQ-9量表，可能存在回忆偏倚，且未区分抑郁的亚型和严重程度。此外，研究结果主要适用于美国高脂血症人群，其在不同种族和文化中的适用性待验证。最后，数据缺失可能带来偏倚。
本研究揭示了高脂血症人群中BRI与抑郁风险的U型关系，并确定了阈值；阈值以下，BRI增加与抑郁风险降低相关；阈值以上，BRI增加则与抑郁风险升高相关。
基金
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  • 河北省科技厅科研基金(22557760K)
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2025年第52卷第19期
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doi: 10.20043/j.cnki.MPM.202504437
  • 接收时间：2025-04-25
  • 首发时间：2026-03-17
  • 出版时间：2025-10-10
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  • 收稿日期：2025-04-25
基金
河北省科技厅科研基金(22557760K)
作者信息
    1.首都医科大学医学附属北京朝阳医院神经内科，北京 100043
    2.河北北方学院附属第一医院神经内科
    3.昆明市第三人民医院公共检验科/云南省传染病临床医学中心

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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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