Article(id=1241342459779805297, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241342451043061769, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202312222, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1702396800000, receivedDateStr=2023-12-13, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773888705438, onlineDateStr=2026-03-19, pubDate=1708790400000, pubDateStr=2024-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773888705438, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773888705438, creator=13701087609, updateTime=1773888705438, updator=13701087609, issue=Issue{id=1241342451043061769, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='4', pageStart='577', pageEnd='768', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773888703356, creator=13701087609, updateTime=1773893026321, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241360582939562716, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241342451043061769, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241360582939562717, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241342451043061769, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=607, endPage=612, ext={EN=ArticleExt(id=1241342460224401559, articleId=1241342459779805297, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Associations between obesity and non-alcoholic fatty liver disease and the mediating role of hyperuricemia in the occupational population, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the association between obesity and non-alcoholic fatty liver disease (NAFLD) in the occupational population, and the mediating role played by hyperuricemia in the association, to provide reference for the prevention and intervention strategies of NAFLD in the occupational population.

Methods

Multistage cluster sampling was used to survey occupational population in Chongqing Municipality, Sichuan Province, and Guizhou Province to obtain social and demographic indicators, lifestyle and health status indicators, and to collect physical examination indicators from the survey respondents. The correlation between obesity and NAFLD was analyzed by Spearman’s rank correlation coefficient and multivariable adjusted Logistic regression. The mediating effect of hyperuricemia in the association between obesity and NAFLD was explored by mediating effect model.

Results

A total of 15 029 study participants who met the inclusion criteria were enrolled, including 1 190 patients with NAFLD. The results of Logistic regression showed that, after adjusting for covariates such as age and gender, obesity increased the risk of NAFLD (OR=3.37, 95% CI: 2.78 to 4.09) and was associated with higher risk of NAFLD in those aged <45 years (OR=3.93, 95% CI: 3.12 to 4.94) and female subgroups (OR=3.65, 95% CI: 1.98 to 6.71) had greater effect values for the effect of obesity on NAFLD. The mediation analysis found that hyperuricemia mediated 11.72% of the effect between obesity and NAFLD, and in the subgroup analysis, the mediation effect of hyperuricemia was higher in the female subgroups (23.81%).

Conclusion

Obesity is strongly associated with the incident of NAFLD, with a greater effect in younger and female groups, and affects NAFLD through hyperuricemia. Strengthening the preventive education of obesity and hyperuricemia and advocating a healthy lifestyle may be effective in reducing NAFLD caused by obesity and hyperuricemia.

, correspAuthors=null, 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, authorCompany=null, fund=null, authors=null, authorsList=Xu QIAO, Yu-qi HU, Yun-zhe FAN, Ting-ting YE, Chun-lan MA, Chang-wei CAI, Shu-juan YANG, JAN D. Reinhardt, Bo YANG), CN=ArticleExt(id=1241342463470793040, articleId=1241342459779805297, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=职业人群肥胖与非酒精性脂肪肝关联及高尿酸血症的中介作用分析, columnId=1228016571273113811, journalTitle=现代预防医学, columnName=环境与职业卫生, runingTitle=null, highlight=null, articleAbstract=
目的

探究职业人群肥胖与非酒精性脂肪肝的关联,以及高尿酸血症在关联路径中的中介作用,为职业人群非酒精性脂肪肝的预防与干预策略提供参考。

方法

采用多阶段整群抽样,基于西南职业人群队列,通过问卷调查获取调查对象社会人口学指标、生活方式等信息,并获取其体检信息。通过 Spearman 秩相关系数和logistic回归分析肥胖与非酒精性脂肪肝之间的相关关系。通过中介效应模型探讨高尿酸血症在肥胖与非酒精性脂肪肝关联中的中介效应。

结果

共纳入15 029例研究对象,其中新发非酒精性脂肪肝患者1 190人。Logistic回归结果显示,调整年龄、性别等协变量后,肥胖会增加非酒精性脂肪肝发生的风险(OR=3.37, 95% CI: 2.78~4.09),且年龄<45岁人群(OR=3.93, 95% CI: 3.12~4.94)和女性亚组(OR=3.65, 95% CI: 1.98~6.71)中肥胖对非酒精性脂肪肝发生风险的影响更大。中介分析发现,高尿酸血症在肥胖与非酒精性脂肪肝之间的中介效应占比为 11.72%,亚组分析中,女性亚组高尿酸血症中介效应占比更高(23.81%)。

结论

肥胖与非酒精性脂肪肝的发生密切相关,在年轻人和女性群体影响更大,并会通过高尿酸血症影响非酒精性脂肪肝。加强肥胖和高尿酸血症的预防教育,倡导健康的生活方式或可减少肥胖与高尿酸血症导致的非酒精性脂肪肝。

, correspAuthors=null, authorNote=null, correspAuthorsNote=
杨波,E-mail:
Jan D. Reinhardt,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=GAex147LndzWAcgIBZXn3Q==, magXml=f+tgoUT/IRLtwcLPe8Nr9A==, pdfUrl=null, pdf=PKXxzuoDD4bh/yvEM59kMQ==, pdfFileSize=1020151, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=GDB28LKxGbdcVrsJmAkIiQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=HTVMOjODjJddU8XHWaJOHA==, mapNumber=null, authorCompany=null, fund=null, authors=

乔栩(1997—),男,硕士在读,研究方向:流行病学

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乔栩(1997—),男,硕士在读,研究方向:流行病学

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乔栩(1997—),男,硕士在读,研究方向:流行病学

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4.成都大学附属医院
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注:A,总人群;B,< 45岁人群;C,≥ 45岁人群;D,男性;E,女性。

, figureFileSmall=J4D4BMtvFNrAOb8YUnpa9g==, figureFileBig=GpAbmLoBJAPZlxMkOQNzsQ==, tableContent=null), ArticleFig(id=1241359970772513786, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459779805297, language=EN, label=Table 1, caption=

Basic characteristics of the study participants

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人数 (n=15 029)非NAFLD(n=13 839)NAFLD(n=1 190)P
社会人口学特征
年龄(岁)35.2(10.2)35.1(10.2)36.5(10.5)<0.001
性别
11 658(77.6)10 574(76.4)1 084(91.1)<0.001
3 371(22.4)3 265(23.6)106(8.9)
婚姻状况
未婚5 365(35.7)4 975(35.9)390(32.8)0.031
已婚9 664(64.3)8 864(64.1)800(67.2)
教育程度
高中及以下3 455(23.0)3 125(22.6)330(27.7)<0.001
高中以上11 574(77.0)10 714(77.4)860(72.3)
家庭月收入(元)
<3 000671(4.5)620(4.5)51(4.3)0.150
3 000~5 9994 612(30.7)4 249(30.7)363(30.5)
6 000~10 0006 770(45.0)6 203(44.8)567(47.6)
>10 0002 976(19.8)2 767(20.0)209(17.6)
工种
后勤、管理人员5 207(34.6)4 829(34.9)378(31.8)<0.001
技术人员、工人5 353(35.6)4 865(35.2)488(41.0)
司机、列车乘务员4 469(29.7)4 145(30.0)324(27.2)
生活方式
体力活动水平
4 535(30.2)4 208(30.4)327(27.5)0.099
5 384(35.8)4 947(35.7)437(36.7)
5 110(34.0)4 684(33.8)426(35.8)
膳食状况
468(3.1)437(3.2)31(2.6)0.065
一般8 537(56.8)7 824(56.5)713(59.9)
6 024(40.1)5 578(40.3)446(37.5)
吸烟
不吸烟8 344(55.5)7 761(56.1)583(49.0)<0.001
吸烟6 685(44.5)6 078(43.9)607(51.0)
职业昼夜节律
无白班344(2.3)315(2.3)29(2.4)<0.001
无规律上班6 484(43.1)5 957(43.0)527(44.3)
无夜班3 140(20.9)2 948(21.3)192(16.1)
有规律白班夜班交替5 061(33.7)4 619(33.4)442(37.1)
健康状况
肥胖
14 329(95.3)1 3321(96.3)1 008(84.7)<0.001
700(4.7)518(3.7)182(15.3)
高尿酸血症
10 682(71.1)10 063(72.7)616(52.0)<0.001
4 347(28.9)3 776(27.3)571(48.0)
代谢综合征
13 557(90.2)12 662(91.5)895(75.2)<0.001
1 472(9.8)1 177(8.5)295(24.8)
), ArticleFig(id=1241359970839622653, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459779805297, language=CN, label=表1, caption=

研究对象基本特征描述[(),n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人数 (n=15 029)非NAFLD(n=13 839)NAFLD(n=1 190)P
社会人口学特征
年龄(岁)35.2(10.2)35.1(10.2)36.5(10.5)<0.001
性别
11 658(77.6)10 574(76.4)1 084(91.1)<0.001
3 371(22.4)3 265(23.6)106(8.9)
婚姻状况
未婚5 365(35.7)4 975(35.9)390(32.8)0.031
已婚9 664(64.3)8 864(64.1)800(67.2)
教育程度
高中及以下3 455(23.0)3 125(22.6)330(27.7)<0.001
高中以上11 574(77.0)10 714(77.4)860(72.3)
家庭月收入(元)
<3 000671(4.5)620(4.5)51(4.3)0.150
3 000~5 9994 612(30.7)4 249(30.7)363(30.5)
6 000~10 0006 770(45.0)6 203(44.8)567(47.6)
>10 0002 976(19.8)2 767(20.0)209(17.6)
工种
后勤、管理人员5 207(34.6)4 829(34.9)378(31.8)<0.001
技术人员、工人5 353(35.6)4 865(35.2)488(41.0)
司机、列车乘务员4 469(29.7)4 145(30.0)324(27.2)
生活方式
体力活动水平
4 535(30.2)4 208(30.4)327(27.5)0.099
5 384(35.8)4 947(35.7)437(36.7)
5 110(34.0)4 684(33.8)426(35.8)
膳食状况
468(3.1)437(3.2)31(2.6)0.065
一般8 537(56.8)7 824(56.5)713(59.9)
6 024(40.1)5 578(40.3)446(37.5)
吸烟
不吸烟8 344(55.5)7 761(56.1)583(49.0)<0.001
吸烟6 685(44.5)6 078(43.9)607(51.0)
职业昼夜节律
无白班344(2.3)315(2.3)29(2.4)<0.001
无规律上班6 484(43.1)5 957(43.0)527(44.3)
无夜班3 140(20.9)2 948(21.3)192(16.1)
有规律白班夜班交替5 061(33.7)4 619(33.4)442(37.1)
健康状况
肥胖
14 329(95.3)1 3321(96.3)1 008(84.7)<0.001
700(4.7)518(3.7)182(15.3)
高尿酸血症
10 682(71.1)10 063(72.7)616(52.0)<0.001
4 347(28.9)3 776(27.3)571(48.0)
代谢综合征
13 557(90.2)12 662(91.5)895(75.2)<0.001
1 472(9.8)1 177(8.5)295(24.8)
), ArticleFig(id=1241359970965451776, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459779805297, language=EN, label=Table 2, caption=

Associations between obesity and NAFLD

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人群OR(95% CIP调整OR(95% CIP
总人群(n=15 029)
肥胖
1.001.00
4.64(3.88~5.56)<0.0013.37(2.78~4.09)<0.001a
年龄亚组0.006b
年龄< 45 (n=11 080)
肥胖
1.001.00
5.50(4.45~6.81)<0.0013.93(3.12~4.94)<0.001a
年龄≥ 45(n=3 949)
肥胖
1.001.00
3.04(2.16~4.29)<0.0012.25(1.56~3.25)<0.001a
性别亚组0.022b
男性(n=11 658)
肥胖
1.001.00
4.08(3.36~4.94)<0.0013.18(2.59~3.90)<0.001a
女性(n=3 371)
肥胖
1.001.00
9.36(5.54~15.81)<0.0013.65(1.98~6.71)<0.001a
), ArticleFig(id=1241359971070308355, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459779805297, language=CN, label=表2, caption=

肥胖与NAFLD关联分析

, figureFileSmall=null, figureFileBig=null, tableContent=
人群OR(95% CIP调整OR(95% CIP
总人群(n=15 029)
肥胖
1.001.00
4.64(3.88~5.56)<0.0013.37(2.78~4.09)<0.001a
年龄亚组0.006b
年龄< 45 (n=11 080)
肥胖
1.001.00
5.50(4.45~6.81)<0.0013.93(3.12~4.94)<0.001a
年龄≥ 45(n=3 949)
肥胖
1.001.00
3.04(2.16~4.29)<0.0012.25(1.56~3.25)<0.001a
性别亚组0.022b
男性(n=11 658)
肥胖
1.001.00
4.08(3.36~4.94)<0.0013.18(2.59~3.90)<0.001a
女性(n=3 371)
肥胖
1.001.00
9.36(5.54~15.81)<0.0013.65(1.98~6.71)<0.001a
), ArticleFig(id=1241359971166777351, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459779805297, language=EN, label=Table 3, caption=

Spearman correlation between obesity, hyperuricemia and NAFLD

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变量肥胖高尿酸血症NAFLD
肥胖1.00
高尿酸血症0.18a1.00
NAFLD0.21a0.12a1.00
), ArticleFig(id=1241359971242274827, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459779805297, language=CN, label=表3, caption=

肥胖、高尿酸血症与NAFLD之间Spearman相关关系

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变量肥胖高尿酸血症NAFLD
肥胖1.00
高尿酸血症0.18a1.00
NAFLD0.21a0.12a1.00
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职业人群肥胖与非酒精性脂肪肝关联及高尿酸血症的中介作用分析
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乔栩 1, 2 , 胡玉麒 3 , 范云喆 2 , 叶婷婷 2 , 马春兰 2 , 蔡长伟 2 , 杨淑娟 2, 4, 5 , Jan D. Reinhardt 1, 6, 7, 8 , 杨波 4
现代预防医学 | 环境与职业卫生 2024,51(4): 607-612
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现代预防医学 | 环境与职业卫生 2024, 51(4): 607-612
职业人群肥胖与非酒精性脂肪肝关联及高尿酸血症的中介作用分析
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乔栩1, 2, 胡玉麒3, 范云喆2, 叶婷婷2, 马春兰2, 蔡长伟2, 杨淑娟2, 4, 5, Jan D. Reinhardt1, 6, 7, 8 , 杨波4
作者信息
  • 1.四川大学-香港理工大学灾后重建与管理学院,成都 610207
  • 2.四川大学华西公共卫生学院/华西第四医院
  • 3.中国铁路成都局集团有限公司社会保险管理部
  • 4.成都大学附属医院
  • 5.武汉大学空间全生命周期健康国际研究中心
  • 6.南京医科大学第一附属医院江苏省医院康复研究中心
  • 7.瑞士截瘫研究中心
  • 8.卢塞恩大学健康科学与医学系
  • 乔栩(1997—),男,硕士在读,研究方向:流行病学

通讯作者:

杨波,E-mail:
Jan D. Reinhardt,E-mail:
Associations between obesity and non-alcoholic fatty liver disease and the mediating role of hyperuricemia in the occupational population
Xu QIAO1, 2, Yu-qi HU3, Yun-zhe FAN2, Ting-ting YE2, Chun-lan MA2, Chang-wei CAI2, Shu-juan YANG2, 4, 5, JAN D. Reinhardt1, 6, 7, 8 , Bo YANG4
Affiliations
  • Institute for Disaster Management and Reconstruction of Sichuan University and Hong Kong Polytechnic University, Sichuan University, Chengdu, Sichuan 610207, China
出版时间: 2024-02-25 doi: 10.20043/j.cnki.MPM.202312222
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目的

探究职业人群肥胖与非酒精性脂肪肝的关联,以及高尿酸血症在关联路径中的中介作用,为职业人群非酒精性脂肪肝的预防与干预策略提供参考。

方法

采用多阶段整群抽样,基于西南职业人群队列,通过问卷调查获取调查对象社会人口学指标、生活方式等信息,并获取其体检信息。通过 Spearman 秩相关系数和logistic回归分析肥胖与非酒精性脂肪肝之间的相关关系。通过中介效应模型探讨高尿酸血症在肥胖与非酒精性脂肪肝关联中的中介效应。

结果

共纳入15 029例研究对象,其中新发非酒精性脂肪肝患者1 190人。Logistic回归结果显示,调整年龄、性别等协变量后,肥胖会增加非酒精性脂肪肝发生的风险(OR=3.37, 95% CI: 2.78~4.09),且年龄<45岁人群(OR=3.93, 95% CI: 3.12~4.94)和女性亚组(OR=3.65, 95% CI: 1.98~6.71)中肥胖对非酒精性脂肪肝发生风险的影响更大。中介分析发现,高尿酸血症在肥胖与非酒精性脂肪肝之间的中介效应占比为 11.72%,亚组分析中,女性亚组高尿酸血症中介效应占比更高(23.81%)。

结论

肥胖与非酒精性脂肪肝的发生密切相关,在年轻人和女性群体影响更大,并会通过高尿酸血症影响非酒精性脂肪肝。加强肥胖和高尿酸血症的预防教育,倡导健康的生活方式或可减少肥胖与高尿酸血症导致的非酒精性脂肪肝。

肥胖  /  高尿酸血症  /  非酒精性脂肪肝
Objective

To investigate the association between obesity and non-alcoholic fatty liver disease (NAFLD) in the occupational population, and the mediating role played by hyperuricemia in the association, to provide reference for the prevention and intervention strategies of NAFLD in the occupational population.

Methods

Multistage cluster sampling was used to survey occupational population in Chongqing Municipality, Sichuan Province, and Guizhou Province to obtain social and demographic indicators, lifestyle and health status indicators, and to collect physical examination indicators from the survey respondents. The correlation between obesity and NAFLD was analyzed by Spearman’s rank correlation coefficient and multivariable adjusted Logistic regression. The mediating effect of hyperuricemia in the association between obesity and NAFLD was explored by mediating effect model.

Results

A total of 15 029 study participants who met the inclusion criteria were enrolled, including 1 190 patients with NAFLD. The results of Logistic regression showed that, after adjusting for covariates such as age and gender, obesity increased the risk of NAFLD (OR=3.37, 95% CI: 2.78 to 4.09) and was associated with higher risk of NAFLD in those aged <45 years (OR=3.93, 95% CI: 3.12 to 4.94) and female subgroups (OR=3.65, 95% CI: 1.98 to 6.71) had greater effect values for the effect of obesity on NAFLD. The mediation analysis found that hyperuricemia mediated 11.72% of the effect between obesity and NAFLD, and in the subgroup analysis, the mediation effect of hyperuricemia was higher in the female subgroups (23.81%).

Conclusion

Obesity is strongly associated with the incident of NAFLD, with a greater effect in younger and female groups, and affects NAFLD through hyperuricemia. Strengthening the preventive education of obesity and hyperuricemia and advocating a healthy lifestyle may be effective in reducing NAFLD caused by obesity and hyperuricemia.

Obesity  /  Hyperuricemia  /  NAFLD
乔栩, 胡玉麒, 范云喆, 叶婷婷, 马春兰, 蔡长伟, 杨淑娟, Jan D. Reinhardt, 杨波. 职业人群肥胖与非酒精性脂肪肝关联及高尿酸血症的中介作用分析. 现代预防医学, 2024 , 51 (4) : 607 -612 . DOI: 10.20043/j.cnki.MPM.202312222
Xu QIAO, Yu-qi HU, Yun-zhe FAN, Ting-ting YE, Chun-lan MA, Chang-wei CAI, Shu-juan YANG, JAN D. Reinhardt, Bo YANG. Associations between obesity and non-alcoholic fatty liver disease and the mediating role of hyperuricemia in the occupational population[J]. Modern Preventive Medicine, 2024 , 51 (4) : 607 -612 . DOI: 10.20043/j.cnki.MPM.202312222
现有研究表明,肥胖是非酒精性脂肪肝(Non-Alcoholic Fatty Liver Disease, NAFLD)高患病率的首要因素[1]。NAFLD在全球有着高达25%的患病率[2],已成为主要的公共卫生问题,NAFLD的发生不仅会导致肝脏出现严重的病理性改变(如肝硬化和肝细胞癌),也会给除肝脏外的多个系统带来健康负担[3]。高尿酸血症作为一种常见的代谢异常状态,与肥胖也有着密切关联[4-5],并且尿酸水平升高或高尿酸血症可能会进一步增加代谢异常风险,导致NAFLD的发作[6-7],因此,高尿酸血症可能在肥胖与NAFLD间关联中起到中介作用。目前,国内外研究主要聚焦于自然人群中肥胖、血清尿酸与NAFLD的发生关系[8-9],职业人群面临较大的社会和家庭的压力,在肥胖与高尿酸血症高患病率的背景下,有必要探索职业人群肥胖与NAFLD风险的关联性,以及高尿酸血症是否介导该关联过程。本研究基于西南职业人群队列调查数据,旨在分析肥胖与NAFLD发生风险之间的关联,同时探索高尿酸血症在肥胖与NAFLD关联关系中的中介效应。本研究将有助于更好地了解职业人群中肥胖及高尿酸血症在NAFLD发生中的作用,制定合理的预防干预策略。
本研究以中国铁路成都局集团有限公司在中国西南地区的四川、重庆和贵州三省建立的西南职业人群队列为基础。截至2021年,涵盖员工119 780人,来自四川省和贵州省28个市/地,以及重庆市33个区/县。采用系统随机抽样的方法,通过唯一的员工识别号,抽取39 926名在职成年人。在2021 年 10 月 1 日至 12 月 31 日期间通过人事管理部门的网站采用在线自填式问卷收集信息,并获得调查人员体检资料。问卷中使用三个常识性问题来检验问卷是否合格(例如,中国的首都在哪里),如果三个问题中的任何一个回答错误,则该问卷认为无效,共纳入31 105名调查对象。本研究的纳入标准为:1)在岗职工;2)认知能力良好且能正常沟通、知情同意且自愿参加的职工,共25 945人合格参与者。根据问卷和体检信息,以及脂肪肝的定义,共排除3 407名基本信息缺失的参与者,6 026名自我报告为中/重度饮酒或戒酒者,及1 484名既往病毒性肝炎和其他肝病患者,最终有15 029名研究对象被纳入本次研究。本研究已通过四川大学华西第四医院/华西公共卫生学院伦理委员会伦理审查(Gwll2021064)。所有研究对象均自愿参加并签署知情同意书。
根据中国肥胖工作组制定的标准,暴露变量肥胖被定义为体重指数(Body Mass Index, BMI)≥ 28 kg/m2[10]。中介变量高尿酸血症定义为男性血清尿酸水平> 420 μmol/L,女性血清尿酸水平>360 μmol/L[11]。结局变量NAFLD采用腹部超声进行诊断。排除基线患有NAFLD、过度饮酒和/或合并肝病等情况的参与者后,脂肪肝腹部超声检查阳性显示血管模糊、肝回声大于肾回声、肝回声弥漫性增高或“亮肝”、肝远场超声回声逐渐衰减者[12]。本研究还纳入了一般社会人口学资料、行为生活方式、健康状况作为协变量。人口特征包括年龄、性别,收入,教育水平,婚姻状况,职业类型和家庭月收入。行为生活方式包括:体力活动,通过代谢当量任务(Metabolic Equivalent Task, MET)测量[13],分为低体力活动(<600 MET-min/w)、适量(600-2 999 MET-min/w)和高体力活动(≥3 000 MET-min/w);饮食模式,采用食物频率问卷(Food Frequency Questionnaire, FFQ)量表评估,分为理想、中、差三组饮食模式[14];吸烟状态;职业昼夜节律。除肥胖和尿酸情况,健康状况包含是否患有代谢综合征,其定义为有以下三项及以上指标异常[15]:(1)血压升高:收缩压≥130 mmHg或舒张压≥85 mmHg或使用降压药物;(2)空腹血糖(Fasting Plasma Glucose, FPG)升高:FPG水平≥ 5.60 mmol/L,已确诊糖尿病或服用降糖药物患者;(3)甘油三酯(Triglycerides, TG)升高:TG水平≥ 1.7 mmol/L或使用降脂药物;(4)高密度脂蛋白胆固醇(High Density Lipoprotein Cholesterol, HDL-C)降低:HDL-C水平< 1.04 mmol/L,或使用降脂药物;5)男性腰围> 90 cm,女性腰围>85 cm。
连续性变量使用均值(标准差)或中位数(四分位数)进行描述,分类变量使用频数(%)进行描述。采用Spearman秩相关系数分析肥胖、高尿酸血症与NAFLD的相关关系。采用多变量调整的logistic回归模型估计肥胖与NAFLD的关联性,报告OR值与95%置信区间(CI)。参考以往研究[8,16],模型纳入协变量包含年龄,性别,婚姻状况,教育程度,职业与家庭月收入,体力活动,膳食模式,吸烟,职业昼夜节律和代谢综合征患病。采用亚组分析,探讨年龄(<45岁, ≥ 45岁)及性别对肥胖与NAFLD关联性的修饰作用。基于Baron和Kenny准则[17],通过因果逐步回归比较不同模型的系数来检验中介效应,得出总效应,直接效应与间接效应值及其95% CI,并计算中介效应占比 [中介效应占比 = (间接效应/总效应)×100%],Bootstrap法用于进行中介效应的显著性检测,随机抽样1 000次。统计分析使用R 4.2.3进行,中介效应采用R软件“bruceR”包进行分析,检验水准α=0.05。
本研究共调查研究对象31 105人,15 029研究对象符合纳排标准。其中1 190人在2022年中被诊断为NAFLD患者。研究对象平均年龄在35.2±10.2岁,其中11 658人为男性,一半以上研究对象已婚(64.3%)。11 574名研究对象接受过高中及以上的教育,6 770人(45.0%)家庭月收入多在6 000~10 000元,且5 353人(35.6%)为技术人员或工人。NAFLD组与非NAFLD组的体力活动与膳食模式差异无统计学意义;吸烟与职业昼夜节律存在统计学差异。健康状况方面NAFLD组存在肥胖、高尿酸血症患病及代谢综合征患病的比例都更高,组间差异具有统计学意义(均P<0.001)(表1)。
采用单因素及多变量调整logistic回归分析肥胖与NAFLD的关联性,结果发现,肥胖会增加NAFLD发生风险(调整OR=3.37, 95% CI: 2.78~4.09)。亚组分析发现,年龄小于45岁的肥胖人群NAFLD发生风险更高(调整OR=3.93, 95% CI: 3.12~4.94);女性肥胖人群NAFLD发生风险更高(调整OR=3.65, 95% CI: 1.98~6.71)。因此,年龄、性别在肥胖与NAFLD关联关系中均存在调节效应(表2)。
使用Spearman相关性分析发现,肥胖、高尿酸血症与NAFLD间均存在正相关关系(表3)。中介分析结果显示,总人群中高尿酸血症对肥胖相关NAFLD的中介效应具有统计学意义(间接效应OR=1.01,95% CI:1.01~1.02,P<0.001),中介效应占比为11.72%。年龄亚组中,45岁以下人群高尿酸血症对肥胖影响NAFLD的中介效应比例高于45岁以上人群(11.72% vs. 8.49 %)(图1)。女性亚组中,高尿酸血症的中介占比最高,为23.81%;男性亚组高尿酸血症的中介占比为10.00%(图1)。
本研究在两次随访中共有1 190名研究对象被诊断为NAFLD新发患者,调查对象肥胖的患病率为4.7%,高尿酸血症患病率为28.9%,肥胖对于NAFLD的发生风险有影响,且高尿酸血症在肥胖对NAFLD的影响中起到了中介作用。亚组分析发现< 45岁人群和女性受肥胖和高尿酸血症影响更大。
肥胖与NAFLD的发生显著相关,这与先前的研究一致。血清尿酸水平在既往研究中发现是非酒精性脂肪性肝炎的独立预测因素[11]。血清尿酸水平也受肥胖的影响,同时血清尿酸也会与肥胖相互作用影响NAFLD[4,9]。已有的研究表明,当肥胖和高尿酸血症同时存在时,与单独肥胖的影响相比,严重脂肪变性、谷丙转氨酶(Alanine Aminotransferase, ALT)升高和晚期纤维化的几率非常高,高尿酸血症和肥胖的交互作用会显著影响肝脂肪变性和纤维化严重程度[8]。在肥胖影响NAFLD发生的队列研究中发现,血清尿酸水平起到了中介作用[16],与既往研究结果一致,高尿酸血症同样也发现其在肥胖对NAFLD影响中起到中介作用。本研究中高尿酸血症的职业人群患病率为28.9%,高于全国总人群19.03%的患病率[18],因此更应关注该人群中高尿酸血症在肥胖与NAFLD间起到的中介作用。
经典的“两击论”,可以解释高尿酸血症作为中介影响肥胖对NAFLD发生风险的潜在机制[19]。肥胖是促进肝脏脂质积聚的“第一击”;肥胖会引起胰岛素抵抗并增加了肝脏对损伤的易感性。高尿酸血症作为“第二击”,可引起肝细胞损伤的炎症;有研究发现,胰岛素抵抗和高尿酸血症在对某些健康影响的导向性方面表现出共性。胰岛素抵抗诱导高胰岛素血症,通过刺激尿酸盐-阴离子交换导致肾尿酸重吸收增加,因此尿酸从肾小管细胞中排泄减少,尿酸增加,影响对脂肪细胞的促炎作用,并刺激细胞增殖并进一步导致非酒精性脂肪肝炎(Nonalcoholic Steatohepatitis, NASH)和肝纤维化[6,20]
本研究亚组分析表明,年龄改变了肥胖与NAFLD之间的关联,<45岁人群NAFLD发生风险更高,年龄<45岁人群高尿酸血症的中介效应占比要高于≥45岁人群。可能的原因可能是45岁以下的职工比45岁以上的职工由于白夜班交替更多,昼夜节律的紊乱导致更高的代谢相关疾病患病(如代谢综合征患病率为24.8% vs. 8.5%);本研究虽未直接研究昼夜节律与NAFLD的关系,但有研究发现昼夜节律紊乱会显著增加代谢综合征的患病风险[21],NAFLD作为与代谢综合征高度相关疾病,因此也会影响NAFLD的发生与进展。患肥胖的女性发生NAFLD风险更高,且高尿酸血症起到的中介效应占比更高,这与既往研究不一致[16]。可能的原因是女性存在绝经期,虽然性激素对尿酸代谢的直接影响尚不清楚,但有研究表明性激素可能在尿酸代谢中发挥作用,这往往会使女性健康状况更加受影响。例如,绝经期女性痛风风险增加[22],这可能是高尿酸血症在女性群体中介效应更高的原因。
本研究有如下局限性。首先,横断面的研究设计与分析限制了因果关系的推论。其次,本研究行为生活方式等数据是通过问卷调查获取,可能存在报告偏倚。最后,研究在西南地区进行,结果的外推性在其他地区受限。综上,肥胖患病与NAFLD发生显著相关,并会通过高尿酸血症增加NAFLD的发生风险。应加强对年轻职工与女性的健康管理,定期开展健康体检,倡导健康的生活方式,提倡肥胖与高尿酸血症的一级预防,从而减少因肥胖和高尿酸血症造成的NAFLD。
  • 国家重点研发计划(2023YFC3604702)
  • 国家自然科学基金(42271433)
  • 四川省重点研发项目(2023YFS0251)
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2024年第51卷第4期
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doi: 10.20043/j.cnki.MPM.202312222
  • 接收时间:2023-12-13
  • 首发时间:2026-03-19
  • 出版时间:2024-02-25
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  • 收稿日期:2023-12-13
基金
国家重点研发计划(2023YFC3604702)
国家自然科学基金(42271433)
四川省重点研发项目(2023YFS0251)
作者信息
    1.四川大学-香港理工大学灾后重建与管理学院,成都 610207
    2.四川大学华西公共卫生学院/华西第四医院
    3.中国铁路成都局集团有限公司社会保险管理部
    4.成都大学附属医院
    5.武汉大学空间全生命周期健康国际研究中心
    6.南京医科大学第一附属医院江苏省医院康复研究中心
    7.瑞士截瘫研究中心
    8.卢塞恩大学健康科学与医学系

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2种不同金属材料的力学参数

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属数
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genus
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species
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Percentage of
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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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