Article(id=1240738483883528640, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202411214, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1731427200000, receivedDateStr=2024-11-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773744706363, onlineDateStr=2026-03-17, pubDate=1746806400000, pubDateStr=2025-05-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773744706363, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773744706363, creator=13701087609, updateTime=1773744706363, updator=13701087609, issue=Issue{id=1240738480549065614, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='9', pageStart='1537', pageEnd='1728', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773744705569, creator=13701087609, updateTime=1773744787657, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240738824918192654, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240738824922386959, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1669, endPage=1673, ext={EN=ArticleExt(id=1240738484198101460, articleId=1240738483883528640, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study on the association between weight-adjusted waist index and chronic kidney disease in the middle-aged and elderly population in China, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the relationship between the weight-adjusted waist index (WWI) and chronic kidney disease (CKD) among the middle-aged and elderly population in China.

Methods

This study included 5 630 individuals aged 45 and older who participated in the China Health and Retirement Longitudinal Survey (CHARLS) in 2011 and 2015. The Cox proportional hazards regression model was employed to analyze the association between WWI, treated as a continuous variable and categorized into quartiles, and the risk of CKD. Additionally, a restricted cubic spline (RCS) model was used to explore the dose-response relationship between WWI and CKD.

Results

During the four-year follow-up, 187 participants developed CKD,resulting in an incidence rate of 3.32%. After adjusting for all covariates, each unit increase in WWI was associated with a 33%increase in the risk of CKD (HR: 1.33, 95%CI: 1.10-1.62). In the highest quartile of WWI, the risk of CKD was 2.30 times greater compared to the lowest quartile (HR=2.30, 95%CI: 1.37-3.86). The RCS curve indicated a nonlinear dose-response relationship between WWI and CKD (Pfornon-linear < 0.05).

Conclusion

There is a positive correlation between WWI and the risk of CKD among the middle-aged and elderly population in China, exhibiting a significant nonlinear dose-response relationship.

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目的

了解中国中老年人群体重矫正腰围指数(weight-adjusted-waist index, WWI)与慢性肾病(chronic kidney disease, CKD)之间的关系。

方法

本研究纳入了2011和2015年参加中国健康与养老追踪调查(China Health and Retirement Longitudinal Survey, CHARLS)的5 630名45岁及以上的中老年人,采用Cox比例风险回归模型分析WWI作为连续变量及四分位数分组与CKD发病风险的关系。进一步使用限制性立方样条(restricted cubic spline, RCS)模型探讨WWI与CKD之间的剂量-反应关系。

结果

在四年随访中,共有187名参与者发生CKD,发病率为3.32%。调整所有协变量后,WWI每增加1个单位,CKD的发生风险增加33%(HR=1.33,95%CI: 1.10~1.62)。在WWI水平最高的四分位组中,CKD的发生风险较最低四分位组增加2.30倍(HR=2.30,95%CI: 1.37~3.86)。RCS曲线显示,WWI与CKD之间存在非线性剂量-反应关系(P fornonlinear<0.05)。

结论

WWI与中国中老年人群发生CKD的风险呈正相关,并且表现出显著的非线性剂量-反应关系。

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黎燕宁,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=AMcjXx/Pmf9RxXDs3lNrBQ==, magXml=tTMGATB1FCNWY7yhPYBdeQ==, pdfUrl=null, pdf=3LzR+8Tq0GHy6Kudo7rbug==, pdfFileSize=592800, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=MxsgaBiSOlL/ng0MpHYa2w==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=S58ZZyETtkOwfMJEtlO7Gw==, mapNumber=null, authorCompany=null, fund=null, authors=

覃晓莹与梁炎炎为共同第一作者

覃晓莹(1998—),女,硕士在读,研究方向:流行病与卫生统计学

梁炎炎(1999—),男,硕士在读,研究方向:流行病与卫生统计学

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覃晓莹(1998—),女,硕士在读,研究方向:流行病与卫生统计学

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Basic characteristics of participants stratified by WWI quartile [MP25P75),n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总计
n=5 630)
Q1(n=1 408)
(≤10.70
Q2(n=1 407)
(10.71~11.20
Q3(n=1 407)
(11.21~11.74
Q4(n=1 408)
(≥11.75
H/χ2P
年龄(岁)58.0(51.0,64.0)56.0(50.0,62.0)56.0(50.0,62.0)58.0(51.0,64.0)60.0(54.0,67.0)181.00<0.001
性别
2 929(52.02)401(28.48)558(39.66)808(57.43)1 162(82.53)940.28<0.001
2 701(47.98)1 007(71.52)849(60.34)599(42.57)246(17.47)
婚姻
其他542(9.63)110(7.81)107(7.60)110(7.82)215(15.27)68.77<0.001
已婚5 088(90.37)1 298(92.19)1 300(92.40)1 297(92.18)1 193(84.73)
居住地
城市1 908(33.89)426(30.26)469(33.33)514(36.53)499(35.44)14.390.002
农村3 722(66.11)982(69.74)938(66.66)893(63.47)909(64.56)
教育程度
小学以下2 585(45.91)541(38.43)535(38.02)656(46.62)853(60.58)
小学1 278(22.70)322(22.87)341(24.24)323(22.96)292(20.74)225.12<0.001
中学1 203(21.37)373(26.49)358(25.44)279(19.83)193(13.71)
高中及以上564(10.02)172(12.22)173(12.30)149(10.59)70(4.97)
饮酒史
3 373(59.91)689(48.93)733(52.10)892(63.40)1 059(75.21)250.79<0.001
2 257(40.09)719(51.07)674(47.90)515(36.60)349(24.79)
吸烟史
3 417(60.69)602(42.76)735(52.24)937(66.60)1 143(81.18)500.28<0.001
2 213(39.31)806(57.24)672(47.76)470(33.40)265(18.82)
CKD
5 443(96.68)1 384(98.30)1 367(97.16)1 356(96.38)1 336(94.89)26.95<0.001
187(3.32)24(1.70)40(2.84)51(3.62)72(5.11)
体重(kg)58.9(52.3,66.5)57.3(51.3,63.8)60.6(53.0,68.2)60.1(53.0,68.0)58.1(51.8,66.2)73.22<0.001
腰围(cm)86.4(79.6,93.2)77.0(72.4,82.4)85.0(80.0,90.5)89.0(83.2,94.5)94.0(88.5,99.6)2 167.30<0.001
BMI(kg/m2)23.6(21.3,26.1)21.6(19.9,23.7)23.4(21.3,25.7)24.5(22.2,26.7)25.1(22.8,27.7)754.42<0.001
CRP(mg/L)9.8(5.4,20.1)7.9(4.5,16.1)9.1(5.0,19.1)10.4(5.7,21.9)12.3(6.7,24.8)134.30<0.001
身高(m)1.58(1.52,1.64)1.63(1.57,1.68)1.60(1.55,1.66)1.57(1.52,1.62)1.52(1.48,1.57)1 204.30<0.001
血尿酸(μmol/L)252.71
(210.84,302.25)
257.61(213.69,304.53)258.41(213.64,307.87)251.81(210.00,304.23)243.02
(207.55,292.98)
32.33<0.001
血肌酐(μmol/L)65.93(56.94,76.92)69.92(60.93,79.91)67.93(58.94,77.92)64.93(55.94,75.92)61.93(54.94,69.92)253.75<0.001
BUN(mmol/L)5.36(4.48,6.40)5.46(4.56,6.54)5.42(4.49,6.46)5.33(4.46,6.37)5.23(4.43,6.27)16.64<0.001
HDL-C(mmol/L)1.27(1.04,1.53)1.34(1.10,1.61)1.27(1.04,1.55)1.24(1.01,1.48)1.22(1.01,1.47)81.85<0.001
LDL-C(mmol/L)2.94(2.40,3.54)2.84(2.29,3.38)2.88(2.38,3.48)3.02(2.44,3.59)3.08(2.50,3.72)64.87<0.001
葡萄糖(mmol/L)5.67(5.23,6.24)5.59(5.15,6.07)5.65(5.23,6.25)5.68(5.26,6.25)5.74(5.30,6.37)44.87<0.001
TG(mmol/L)1.19(0.85,1.74)0.99(0.74,1.45)1.16(0.84,1.69)1.23(0.89,1.85)1.35(0.98,1.93)233.09<0.001
TC(mmol/L)4.91(4.31,5.56)4.74(4.19,5.37)4.89(4.27,5.51)4.96(4.39,5.56)5.07(4.42,5.73)80.35<0.001
), ArticleFig(id=1241081882369126810, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738483883528640, language=CN, label=表1, caption=

按WWI四分位数分层的参与者基本特征[MP25P75),n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总计
n=5 630)
Q1(n=1 408)
(≤10.70
Q2(n=1 407)
(10.71~11.20
Q3(n=1 407)
(11.21~11.74
Q4(n=1 408)
(≥11.75
H/χ2P
年龄(岁)58.0(51.0,64.0)56.0(50.0,62.0)56.0(50.0,62.0)58.0(51.0,64.0)60.0(54.0,67.0)181.00<0.001
性别
2 929(52.02)401(28.48)558(39.66)808(57.43)1 162(82.53)940.28<0.001
2 701(47.98)1 007(71.52)849(60.34)599(42.57)246(17.47)
婚姻
其他542(9.63)110(7.81)107(7.60)110(7.82)215(15.27)68.77<0.001
已婚5 088(90.37)1 298(92.19)1 300(92.40)1 297(92.18)1 193(84.73)
居住地
城市1 908(33.89)426(30.26)469(33.33)514(36.53)499(35.44)14.390.002
农村3 722(66.11)982(69.74)938(66.66)893(63.47)909(64.56)
教育程度
小学以下2 585(45.91)541(38.43)535(38.02)656(46.62)853(60.58)
小学1 278(22.70)322(22.87)341(24.24)323(22.96)292(20.74)225.12<0.001
中学1 203(21.37)373(26.49)358(25.44)279(19.83)193(13.71)
高中及以上564(10.02)172(12.22)173(12.30)149(10.59)70(4.97)
饮酒史
3 373(59.91)689(48.93)733(52.10)892(63.40)1 059(75.21)250.79<0.001
2 257(40.09)719(51.07)674(47.90)515(36.60)349(24.79)
吸烟史
3 417(60.69)602(42.76)735(52.24)937(66.60)1 143(81.18)500.28<0.001
2 213(39.31)806(57.24)672(47.76)470(33.40)265(18.82)
CKD
5 443(96.68)1 384(98.30)1 367(97.16)1 356(96.38)1 336(94.89)26.95<0.001
187(3.32)24(1.70)40(2.84)51(3.62)72(5.11)
体重(kg)58.9(52.3,66.5)57.3(51.3,63.8)60.6(53.0,68.2)60.1(53.0,68.0)58.1(51.8,66.2)73.22<0.001
腰围(cm)86.4(79.6,93.2)77.0(72.4,82.4)85.0(80.0,90.5)89.0(83.2,94.5)94.0(88.5,99.6)2 167.30<0.001
BMI(kg/m2)23.6(21.3,26.1)21.6(19.9,23.7)23.4(21.3,25.7)24.5(22.2,26.7)25.1(22.8,27.7)754.42<0.001
CRP(mg/L)9.8(5.4,20.1)7.9(4.5,16.1)9.1(5.0,19.1)10.4(5.7,21.9)12.3(6.7,24.8)134.30<0.001
身高(m)1.58(1.52,1.64)1.63(1.57,1.68)1.60(1.55,1.66)1.57(1.52,1.62)1.52(1.48,1.57)1 204.30<0.001
血尿酸(μmol/L)252.71
(210.84,302.25)
257.61(213.69,304.53)258.41(213.64,307.87)251.81(210.00,304.23)243.02
(207.55,292.98)
32.33<0.001
血肌酐(μmol/L)65.93(56.94,76.92)69.92(60.93,79.91)67.93(58.94,77.92)64.93(55.94,75.92)61.93(54.94,69.92)253.75<0.001
BUN(mmol/L)5.36(4.48,6.40)5.46(4.56,6.54)5.42(4.49,6.46)5.33(4.46,6.37)5.23(4.43,6.27)16.64<0.001
HDL-C(mmol/L)1.27(1.04,1.53)1.34(1.10,1.61)1.27(1.04,1.55)1.24(1.01,1.48)1.22(1.01,1.47)81.85<0.001
LDL-C(mmol/L)2.94(2.40,3.54)2.84(2.29,3.38)2.88(2.38,3.48)3.02(2.44,3.59)3.08(2.50,3.72)64.87<0.001
葡萄糖(mmol/L)5.67(5.23,6.24)5.59(5.15,6.07)5.65(5.23,6.25)5.68(5.26,6.25)5.74(5.30,6.37)44.87<0.001
TG(mmol/L)1.19(0.85,1.74)0.99(0.74,1.45)1.16(0.84,1.69)1.23(0.89,1.85)1.35(0.98,1.93)233.09<0.001
TC(mmol/L)4.91(4.31,5.56)4.74(4.19,5.37)4.89(4.27,5.51)4.96(4.39,5.56)5.07(4.42,5.73)80.35<0.001
), ArticleFig(id=1241081882473984414, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738483883528640, language=EN, label=Table 2, caption=

Cox proportional hazards regression analysis of WWI and CKD incidence [HR(95%CI)]

, figureFileSmall=null, figureFileBig=null, tableContent=
WWI四分位分组模型1模型2模型3
HR(95%CIPHR(95%CIPHR(95%CIP
WWI1.57(1.34~1.85)<0.0011.41(1.16~1.70)<0.0011.33(1.10~1.62)0.004
Q11.001.001.00
Q21.68(1.01~2.78)0.0451.70(1.03~2.83)0.0401.64(0.98~2.73)0.058
Q32.15(1.32~3.49)0.0022.04(1.24~3.34)0.0051.90(1.15~3.14)0.012
Q43.05(1.92~4.85)<0.0012.62(1.57~4.35)<0.0012.30(1.37~3.86)0.002
Pfor trend<0.001<0.001<0.001
), ArticleFig(id=1241081882562064799, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738483883528640, language=CN, label=表2, caption=

WWI与CKD发病的Cox比例风险回归模型分析[HR(95%CI)]

, figureFileSmall=null, figureFileBig=null, tableContent=
WWI四分位分组模型1模型2模型3
HR(95%CIPHR(95%CIPHR(95%CIP
WWI1.57(1.34~1.85)<0.0011.41(1.16~1.70)<0.0011.33(1.10~1.62)0.004
Q11.001.001.00
Q21.68(1.01~2.78)0.0451.70(1.03~2.83)0.0401.64(0.98~2.73)0.058
Q32.15(1.32~3.49)0.0022.04(1.24~3.34)0.0051.90(1.15~3.14)0.012
Q43.05(1.92~4.85)<0.0012.62(1.57~4.35)<0.0012.30(1.37~3.86)0.002
Pfor trend<0.001<0.001<0.001
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中国中老年人群体重矫正腰围指数与慢性肾病的关联性研究
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覃晓莹 , 梁炎炎 , 朱意琼 , 陈奎冰 , 王焕东 , 杨钧媚 , 黎燕宁
现代预防医学 | 健康与社会行为 2025,52(9): 1669-1673
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现代预防医学 | 健康与社会行为 2025, 52(9): 1669-1673
中国中老年人群体重矫正腰围指数与慢性肾病的关联性研究
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覃晓莹, 梁炎炎, 朱意琼, 陈奎冰, 王焕东, 杨钧媚, 黎燕宁
作者信息
  • 广西医科大学公共卫生学院,广西 南宁 530021
  • 覃晓莹(1998—),女,硕士在读,研究方向:流行病与卫生统计学

    梁炎炎(1999—),男,硕士在读,研究方向:流行病与卫生统计学

通讯作者:

黎燕宁,E-mail:
Study on the association between weight-adjusted waist index and chronic kidney disease in the middle-aged and elderly population in China
Xiao-ying QIN, Yan-yan LIANG, Yi-qiong ZHU, Kui-bing CHEN, Huan-dong WANG, Jun-mei YANG, Yan-ning LI
Affiliations
  • School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
出版时间: 2025-05-10 doi: 10.20043/j.cnki.MPM.202411214
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目的

了解中国中老年人群体重矫正腰围指数(weight-adjusted-waist index, WWI)与慢性肾病(chronic kidney disease, CKD)之间的关系。

方法

本研究纳入了2011和2015年参加中国健康与养老追踪调查(China Health and Retirement Longitudinal Survey, CHARLS)的5 630名45岁及以上的中老年人,采用Cox比例风险回归模型分析WWI作为连续变量及四分位数分组与CKD发病风险的关系。进一步使用限制性立方样条(restricted cubic spline, RCS)模型探讨WWI与CKD之间的剂量-反应关系。

结果

在四年随访中,共有187名参与者发生CKD,发病率为3.32%。调整所有协变量后,WWI每增加1个单位,CKD的发生风险增加33%(HR=1.33,95%CI: 1.10~1.62)。在WWI水平最高的四分位组中,CKD的发生风险较最低四分位组增加2.30倍(HR=2.30,95%CI: 1.37~3.86)。RCS曲线显示,WWI与CKD之间存在非线性剂量-反应关系(P fornonlinear<0.05)。

结论

WWI与中国中老年人群发生CKD的风险呈正相关,并且表现出显著的非线性剂量-反应关系。

体重矫正腰围指数  /  慢性肾病  /  剂量-反应关系
Objective

To investigate the relationship between the weight-adjusted waist index (WWI) and chronic kidney disease (CKD) among the middle-aged and elderly population in China.

Methods

This study included 5 630 individuals aged 45 and older who participated in the China Health and Retirement Longitudinal Survey (CHARLS) in 2011 and 2015. The Cox proportional hazards regression model was employed to analyze the association between WWI, treated as a continuous variable and categorized into quartiles, and the risk of CKD. Additionally, a restricted cubic spline (RCS) model was used to explore the dose-response relationship between WWI and CKD.

Results

During the four-year follow-up, 187 participants developed CKD,resulting in an incidence rate of 3.32%. After adjusting for all covariates, each unit increase in WWI was associated with a 33%increase in the risk of CKD (HR: 1.33, 95%CI: 1.10-1.62). In the highest quartile of WWI, the risk of CKD was 2.30 times greater compared to the lowest quartile (HR=2.30, 95%CI: 1.37-3.86). The RCS curve indicated a nonlinear dose-response relationship between WWI and CKD (Pfornon-linear < 0.05).

Conclusion

There is a positive correlation between WWI and the risk of CKD among the middle-aged and elderly population in China, exhibiting a significant nonlinear dose-response relationship.

Weight-adjusted waist index  /  Chronic kidney disease  /  Dose-response relationship
覃晓莹, 梁炎炎, 朱意琼, 陈奎冰, 王焕东, 杨钧媚, 黎燕宁. 中国中老年人群体重矫正腰围指数与慢性肾病的关联性研究. 现代预防医学, 2025 , 52 (9) : 1669 -1673 . DOI: 10.20043/j.cnki.MPM.202411214
Xiao-ying QIN, Yan-yan LIANG, Yi-qiong ZHU, Kui-bing CHEN, Huan-dong WANG, Jun-mei YANG, Yan-ning LI. Study on the association between weight-adjusted waist index and chronic kidney disease in the middle-aged and elderly population in China[J]. Modern Preventive Medicine, 2025 , 52 (9) : 1669 -1673 . DOI: 10.20043/j.cnki.MPM.202411214
慢性肾脏病(chronic kidney disease, CKD)被定义为肾脏结构或功能异常,持续超过3个月。当肾小球滤过率估计值(estimated glomerular filtration rate, eGFR)<60 ml/(min·1.73m2)或白蛋白/肌酐比值(albumin-to-creatinine ratio, ACR)≥30 mg/g时,可诊断为CKD[1-2]。CKD是全球公认的主要非传染性疾病[3],其发病率持续增长,对全球健康产生重大影响。CKD不仅是全球范围内发病率和死亡率的直接原因,也是导致心血管疾病的重要危险因素[4]。因此,CKD作为一个重要的公共卫生问题,需早期识别并实施预防策略。
既往研究表明,肥胖是全球疾病负担的重要因素,也是CKD最常见的传统危险因素[5]。肥胖通过胰岛素抵抗(insulin resistance, IR)、脂毒性和血压升高等多种机制,增加肾脏疾病的风险[6-7]。体重矫正腰围指数(weight-adjusted-waist index, WWI)是一种新的人体测量指标,它通过结合腰围与体重来评估肥胖[8]。目前国内关于WWI与中老年人CKD发病风险的研究较少,且大多为横断面研究[9],纵向研究相对匮乏。因此,本研究旨在应对传统CKD的危险因素肥胖,确定高风险人群,进而实施预防干预策略。我们将利用纵向研究探讨我国中老年人WWI与CKD之间的关联,以为制定干预策略提供参考。
中国健康与养老追踪调查(China Health and Retirement Longitudinal Survey, CHARLS)研究已获得北京大学生物医学伦理委员会的伦理审查许可(批准号:IRB00001052-11015)[10]。本研究使用CHARLS中2011和2015年两期追踪数据,研究者已依法完成数据使用申请并获得相应授权。本项研究的纳入标准:(1)参与了2011和2015年两次CHARLS调查;(2)年龄45岁及以上;(3)拥有完整的血液学指标和人口统计学等关键信息。排除标准:(1)基线时eGFR<60 ml/(min·1.73m2),即排除了基线时已诊断为CKD的个体;(2)血液学指标和人口统计学等关键变量数据缺失或异常;(3)存在癌症、精神疾病等合并症。根据这些标准,最终共有5 630名参与者被纳入本研究分析。
本研究收集了研究对象的年龄、性别、婚姻状况、居住地、教育程度、吸烟史和饮酒史信息。纳入的指标包括:(1)身体指标:身高、体重和腰围;(2)生化指标:血尿素氮(blood urea nitrogen,BUN)、高密度脂蛋白胆固醇(high-density lipoprotein cholesterol, HDL-C)、低密度脂蛋白胆固醇(low-density lipoprotein, LDL-C)、血尿酸(uric acid)、葡萄糖(glucose)、甘油三酯(triglyceride)、总胆固醇(total cholesterol)、C反应蛋白(C-reactive protein, CRP)和血肌酐(serum creatinine)。
参考2021年无种族差异的慢性肾脏病学流行病学合作方程(CKD-EPI)[11],该方程使用血肌酐水平来估计肾小球滤过率(eGFR)。公式为:。其中,Scr为血肌酐,单位为mg/dl;k是一个常数,女性为0.7,男性为0.9;α为一个指数,女性为-0.241,男性为-0.302;min表示取Scr/k和1中的较小值,max表示取Scr/k和1中的较大值;age为年龄;1.012是一个性别校正因子,仅在女性中乘以1.012,男性则不需要。根据肾脏疾病专家共识[12],使用eGFR来评估肾脏功能:当eGFR<60 ml/(min·1.73m2)时,定义为患有CKD。
身体质量指数(body mass index, BMI)=体重(kg)/身高的二次方(m2)。WWI=腰围(cm)/体重的平方根()。
计数资料以频数和构成比表示,组间比较采用χ2检验。定量资料中,正态分布数据以(均数±标准差)表示,两组间比较使用t检验,多组间比较采用方差分析;非正态分布数据以中位数(M)及四分位数范围(P25P75)表示,两组间差异比较使用U检验,多组间比较则用H检验。采用Cox比例风险模型分析WWI与CKD的发病关系,并将其以连续型变量及分类变量带入模型进行分析,计算风险比(hazard ratio, HR)及95%可信区间(95%confidential interval, 95%CI)。通常情况下,RCS节点数量建议设置为3~5个。其中,WWI为连续变量,根据百分位数(P5P25P75P95[13]选取4个节点,来探讨WWI与CKD之间的剂量-反应关系。所有数据分析均采用R4.4.1完成,双侧检验,检验水准为α=0.05。
本研究共包括5 630名中老年人,中位年龄为58.0岁,男性为2 701人(47.98%),女性为2 929人(52.02%)。在四年的随访时间里,共有187名参与者发生了CKD,发病率为3.32%。WWI的中位数为11.20(10.70,11.74)。根据WWI的四分位数,将研究对象分为四组:Q1组(≤10.70)、Q2组(10.71~11.20)、Q3组(11.21~11.74)和Q4组(≥11.75)。各组的[MP25P75)]分别为:Q1组10.33(10.00,10.54)cm/、 Q2组10.97(10.85,11.09)、Q3组11.45(11.32,11.58)、Q4组12.16(11.94,12.52)。结果显示,WWI从Q1组至Q4组呈逐渐增大的趋势。随着WWI四分位数的增加,腰围、BMI、LDL-C、葡萄糖、TG、TC和CRP值均升高,而身高、BUN、血尿酸、HDL-C和血肌酐值降低。性别、婚姻状况、居住地、教育程度、吸烟史及饮酒史在不同WWI四分位数分组间存在差异,差异具有统计学意义(P<0.05)。此外,我们发现随着WWI逐渐增大,CKD的发病率也呈上升趋势。见表1
将WWI以连续变量引入模型分析,调整协变量后,模型3的结果显示,WWI每增加一个单位,CKD发病风险增加33%(HR=1.33,95%CI: 1.10~1.62)。为进一步探讨WWI与CKD发病率之间的关系,将WWI分为四分位数以分类变量引入模型分析,调整年龄和性别(模型2)后,以Q1组为参照,Q2、Q3和Q4组CKD发病风险逐渐升高,HR(95%CI)分别为1.70(1.03~2.83)、2.04(1.24~3.34)、2.62(1.57~4.35)(P fortrend<0.001)。模型3经过对婚姻、居住地、教育程度等协变量调整之后,WWI在第三和第四四分位(Q3、Q4)时,CKD发生的风险也逐渐升高,HR(95%CI)分别为1.90(1.15~3.14)、2.30(1.37~3.86)(P fortrend<0.001)。见表2
使用RCS模型进一步检查连续型变量WWI与CKD风险的剂量-反应关系,并设定了4个节点。调整混杂因素后,研究结果显示,WWI与CKD发病风险之间存在非线性剂量反应关系(P foroverall<0.05,P fornonlinear<0.05)。当WWI<9.59时,HR值接近1,表明在此范围内WWI的增加对CKD风险的影响不显著。当超过9.59的拐点后,HR值随WWI的增加显著上升,表明更高的WWI水平显著增加CKD的发病风险。见图1
以往研究主要聚焦于BMI和腰围;等传统肥胖指标与CKD之间的关系。BMI反映的是人体整体脂肪含量,但CKD患者有时会出现身体成分的改变(例如,肌肉量减少、内脏脂肪增加)。腰围;则反映腹部脂肪含量,因此这两者在衡量体脂含量方面存在一定的局限性[14-15]。因此,可以表明传统的肥胖指标可能未能全面揭示肥胖与CKD之间的关系。WWI是通过腰围除以体重的平方根计算得出,能够结合腰围;的优势,更好的反映脂肪和肌肉成分[16]。这两项指标在临床实践中很容易获得,大量研究表明,WWI与高血压、糖尿病和中风之间均存在正相关关系[17-19]。因此,本研究采用WWI评估肥胖与中老年人CKD发病风险的相关性。
本研究基于CHARLS采用纵向研究方法评估了我国中老年人WWI与CKD发病风险之间的关联。研究结果显示,较高的WWI水平与CKD发病风险呈正相关,进一步支持了WWI作为一种潜在的CKD风险预测指标的可能性。迄今为止,有关WWI与CKD之间关联的证据较为有限,本研究为首次开展的纵向研究,旨在探索WWI与CKD之间的关系,尤其关注非线性剂量-反应关系。尽管关于WWI与肾功能关系的研究数量相对较少,但已有一些研究提示WWI可能与CKD的发生风险相关。限制性立方样条图能够更直观、准确地描述WWI与CKD之间的关系,并揭示随WWI水平变化,CKD发病风险的变化趋势。本研究的RCS结果显示,WWI与CKD之间存在非线性剂量-反应关系,表明WWI水平的变化对CKD风险的影响并非线性,而是在某些阈值下显著增强。具体而言,当WWI水平处于一定范围内(WWI>9.59)时,WWI水平越高,发生CKD的风险也越高。这一结果与其他研究结果相一致。例如,美国的一项基于全国健康和营养检查调查(National Health and Nutrition Examination Survey, NHANES)的研究也发现,当WWI>9.81时,WWI与CKD的患病率呈正相关,平滑曲线拟合结果同样显示WWI与CKD之间存在非线性关系[20]。此外,新疆的一项横断面研究也表明,WWI与低eGFR存在非线性联系,且当WWI>11.32时,随着WWI的增加,低eGFR的发生风险显著上升[9]。这两项研究的结果均表明,高水平的WWI与CKD或肾功能损害相关,虽然不同研究中WWI的拐点存在差异,但这些差异可能与研究人群、生活方式和地域特征等因素有关。
本研究数据源自CHARLS,该调查凭借其庞大的样本量、较长的随访周期以及高质量的数据,赋予了研究结果较高的可靠性。本研究采用纵向设计,旨在探讨WWI与中老年人群CKD发病风险的关联,相较于横断面研究,提供了更强的证据支持。然而,本研究仍存在局限性。首先,2011和2015年CHARLS血液学检查数据存在较多缺失值,可能导致部分CKD患者未被诊断。其次,研究的目标群体为CHARLS调查对象,因此结论的外部适用性可能受限。此外,由于本研究仅使用了2011和2015年这两个时间点的数据,这在一定程度上限制了对WWI与CKD之间非线性关系的全面探讨。未来研究应考虑增加更多时间点的数据,并应用适当的统计方法,以更全面地探讨WWI与CKD之间的非线性关系,从而弥补本研究的不足。
综上所述,CKD发病风险随WWI的增加而增加。因此,WWI可作为一种潜在的预测指标,用于评估我国中老年人群CKD的发病风险。这一发现进一步凸显了控制肥胖在预防CKD中的关键作用,而WWI作为一种新兴的肥胖评估指标,其重要性不容忽视。未来的研究应持续深入探索WWI在CKD早期预测中的应用潜力,以期更有效地预防和管理CKD,尤其是针对高WWI水平的中老年人群,采取针对性措施降低其CKD发生风险。
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doi: 10.20043/j.cnki.MPM.202411214
  • 接收时间:2024-11-13
  • 首发时间:2026-03-17
  • 出版时间:2025-05-10
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  • 收稿日期:2024-11-13
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    广西医科大学公共卫生学院,广西 南宁 530021

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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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