Article(id=1241342459574276346, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241342451043061769, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202310283, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1697731200000, receivedDateStr=2023-10-20, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773888705389, onlineDateStr=2026-03-19, pubDate=1708790400000, pubDateStr=2024-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773888705389, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773888705389, creator=13701087609, updateTime=1773888705389, 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=742, endPage=747, ext={EN=ArticleExt(id=1241342459964346646, articleId=1241342459574276346, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Associations of lifestyle scores with nonalcoholic fatty liver disease, columnId=1228016573156360233, journalTitle=Modern Preventive Medicine, columnName=Disease Control and Prevention, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze and explore the association between lifestyle scores and the risk of developing nonalcoholic fatty liver disease (NAFLD) in the United States (US) population, and to provide new ideas for the prevention and treatment of NAFLD.

Methods

The samples of this study were collected from the 2007-2018 US National Health and Nutrition Examination Survey (NHANES) database. Logistic regression analysis was employed to assess the impact of healthy lifestyle and NAFLD. Further stratified analyses were conducted to investigate potential differences across gender, age, ethnicity, marital status, and education levels.

Results

A total of 4 105 participants were included in this study, comprising 1 284 individuals with NAFLD (24.64%) and 2 821 individuals without NAFLD (75.36%). Compared to low lifestyle score, individuals with moderate (OR=0.372, 95% CI: 0.25-0.56, P=9.15×10-6) and high lifestyle score (OR=0.091, 95% CI: 0.06-0.14, P=1.50×10-17) had a lower risk of developing NAFLD. Stratified analyses revealed that this effect was more pronounced among males and individuals aged 60 and above.

Conclusion

Healthy lifestyle is associated with a decreased risk of NAFLD, and improving lifestyle score can be effective in preventing and treating NAFLD.

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目的

基于美国健康与营养调查(NHANES)数据库,探讨生活方式评分与非酒精性脂肪肝(NAFLD)患病之间的关联,为预防和治疗NAFLD提供新思路。

方法

本研究基于2007—2018年的美国NHANES人群数据,通过logistic回归分析评估生活方式对NAFLD的影响。进一步通过分层分析,探讨性别、年龄、种族、婚姻状态、教育程度等不同分层之间的差异。

结果

本研究共纳入4 105名参与者,其中1 284名NAFLD(24.64%),2 821名非NAFLD(75.36%)。研究发现相较于低生活方式评分,生活方式评分中等(OR=0.372,95% CI:0.25~0.56,P=9.15×10-6)和较高(OR=0.091,95% CI:0.06~0.14,P=1.50×10-17)的人群发生NAFLD的风险更低。分层分析显示,该效应在男性和60岁以上人群中更强。

结论

健康生活方式与较低的NAFLD发生风险有关,通过干预生活方式可以有效防治NAFLD。

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叶丁,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=0mFlg3ZpY2aAIGD0cMD/Yg==, magXml=y/iXe846EPxNlUr0Nq18wA==, pdfUrl=null, pdf=sOeiK5fPuvXuVySj6H9rYQ==, pdfFileSize=1342046, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=zhY+Tuk2nguCabMVtDf+kQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=p5f0GJogkh0qhyI+GwgzWA==, mapNumber=null, authorCompany=null, fund=null, authors=

陈颖(1999—),女,硕士在读,研究方向:流行病学工作

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Archives of Gerontology and Geriatrics, 2016, 67: 130-138., articleTitle=Multimorbidity and mortality in older adults: A systematic review and meta-analysis, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1241342463592419790, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, xref=null, ext=[AuthorCompanyExt(id=1241342463600808400, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, companyId=1241342463592419790, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of PublicHealth, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China), AuthorCompanyExt(id=1241342463609197009, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, companyId=1241342463592419790, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=浙江中医药大学公共卫生学院,杭州 浙江 310053)])], figs=[ArticleFig(id=1241342466037699239, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=EN, label=Fig.1, caption=Flow chart of patient screening in the NHANES database, figureFileSmall=pUaRak0RBbESsifebR/kdA==, figureFileBig=zhY+Tuk2nguCabMVtDf+kQ==, tableContent=null), ArticleFig(id=1241342467585397422, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=CN, label=图1, caption=研究对象的筛选流程图, figureFileSmall=pUaRak0RBbESsifebR/kdA==, figureFileBig=zhY+Tuk2nguCabMVtDf+kQ==, tableContent=null), ArticleFig(id=1241342467858027199, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=EN, label=Fig.2, caption=Results of stratified analysis based on demographic characteristics, figureFileSmall=BqQfroN/KIjmq9AFKs0glw==, figureFileBig=KYWI3b+XeNSDICd/RzaWfQ==, tableContent=null), ArticleFig(id=1241342467975467719, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=CN, label=图2, caption=根据人口学特征进行分层分析的结果, figureFileSmall=BqQfroN/KIjmq9AFKs0glw==, figureFileBig=KYWI3b+XeNSDICd/RzaWfQ==, tableContent=null), ArticleFig(id=1241342468172600013, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=EN, label=Table 1, caption=

General baseline characteristics of the participants

, figureFileSmall=null, figureFileBig=null, tableContent=
变量N未调整权重的样本加权后样本
病例组对照组病例组对照组P病例组对照组P
性别(%)
8611 55167.155.0<0.00166.153.7<0.001
4231 27032.945.033.946.3
年龄(岁)1 2842 82159.0(24.0)50.0(29.0)<0.00157.0(23.0)49.0(26.0)<0.001
种族(%)
非西班牙裔白人6751 30452.646.2<0.00177.972.7<0.001
非西班牙裔黑人15164711.822.98.13.8
墨西哥裔美国人22022017.17.83.84.2
其他非西班牙裔1182389.28.45.010.6
其他种族1204129.314.65.28.6
婚姻状态(%)
已婚8091 63163.057.80.00268.163.40.073
未婚4751 19037.042.431.936.6
教育水平(%)
<高中25739720.014.1<0.00113.18.10.001
高中27753321.618.920.118.6
>高中7501 89158.467.066.873.3
腰围(cm)1 2842 821111.4(18.7)92.2(16.3)<0.001112.7(18.3)92.4(16.1)<0.001
葡萄糖(mg/dl)1 2842 821104.0(26.0)92.0(13.0)<0.001102.0(20.0)92.0(12.0)<0.001
胰岛素(pmol/l)1 2842 821112.4(75.4)43.3(31.0)<0.001110.5(68.2)42.2(28.9)<0.001
ALT(U/L)1 2842 82125(15)19(10)<0.00126(15)19(9)<0.001
AST(U/L)1 2842 82124(9)22(7)<0.00124(8)22(7)<0.001
GGT(IU/L)1 2842 82127(22)17(11)<0.00127(19)16(10)<0.001
HDL(mmol/l)1 2842 8211.1(0.4)1.4(0.5)<0.0011.1(0.4)1.5(0.4)<0.001
总胆固醇(mmol/l)1 2842 8214.9(1.4)4.9(1.4)0.2294.9(1.4)4.9(1.4)0.283
), ArticleFig(id=1241342468382315220, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=CN, label=表1, caption=

NAFLD组和非NAFLD组的基本特征比较

, figureFileSmall=null, figureFileBig=null, tableContent=
变量N未调整权重的样本加权后样本
病例组对照组病例组对照组P病例组对照组P
性别(%)
8611 55167.155.0<0.00166.153.7<0.001
4231 27032.945.033.946.3
年龄(岁)1 2842 82159.0(24.0)50.0(29.0)<0.00157.0(23.0)49.0(26.0)<0.001
种族(%)
非西班牙裔白人6751 30452.646.2<0.00177.972.7<0.001
非西班牙裔黑人15164711.822.98.13.8
墨西哥裔美国人22022017.17.83.84.2
其他非西班牙裔1182389.28.45.010.6
其他种族1204129.314.65.28.6
婚姻状态(%)
已婚8091 63163.057.80.00268.163.40.073
未婚4751 19037.042.431.936.6
教育水平(%)
<高中25739720.014.1<0.00113.18.10.001
高中27753321.618.920.118.6
>高中7501 89158.467.066.873.3
腰围(cm)1 2842 821111.4(18.7)92.2(16.3)<0.001112.7(18.3)92.4(16.1)<0.001
葡萄糖(mg/dl)1 2842 821104.0(26.0)92.0(13.0)<0.001102.0(20.0)92.0(12.0)<0.001
胰岛素(pmol/l)1 2842 821112.4(75.4)43.3(31.0)<0.001110.5(68.2)42.2(28.9)<0.001
ALT(U/L)1 2842 82125(15)19(10)<0.00126(15)19(9)<0.001
AST(U/L)1 2842 82124(9)22(7)<0.00124(8)22(7)<0.001
GGT(IU/L)1 2842 82127(22)17(11)<0.00127(19)16(10)<0.001
HDL(mmol/l)1 2842 8211.1(0.4)1.4(0.5)<0.0011.1(0.4)1.5(0.4)<0.001
总胆固醇(mmol/l)1 2842 8214.9(1.4)4.9(1.4)0.2294.9(1.4)4.9(1.4)0.283
), ArticleFig(id=1241342468516532957, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=EN, label=Table 2, caption=

Comparison of lifestyle factors in NAFLD and non-NAFLD groups

, figureFileSmall=null, figureFileBig=null, tableContent=
变量病例组(n=1 284)对照组(n=2 812)P
BMI(%)
≥3028.116.8<0.001
<3071.983.2
吸烟(%)
44.637.40.001
55.462.6
饮酒(%)
87.790.00.062
12.310.0
睡眠时间(%)
<6 h10.18.60.269
≥6 h89.991.4
饮食(%)
健康68.981.9<0.001
不健康31.118.1
适度体育锻炼(%)
45.281.90.001
54.847.0
高血压(%)
52.324.8<0.001
47.775.2
糖尿病(%)
18.95.1<0.001
81.194.9
生活方式评分4.0(2.0)6.0(1.0)<0.001
健康生活方式分组(%)
不健康生活方式8.81.8<0.001
中等健康生活方式72.842.7
不健康生活方式18.555.5
), ArticleFig(id=1241342468659139304, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=CN, label=表2, caption=

NAFLD组与非NAFLD组各生活方式因素的比较

, figureFileSmall=null, figureFileBig=null, tableContent=
变量病例组(n=1 284)对照组(n=2 812)P
BMI(%)
≥3028.116.8<0.001
<3071.983.2
吸烟(%)
44.637.40.001
55.462.6
饮酒(%)
87.790.00.062
12.310.0
睡眠时间(%)
<6 h10.18.60.269
≥6 h89.991.4
饮食(%)
健康68.981.9<0.001
不健康31.118.1
适度体育锻炼(%)
45.281.90.001
54.847.0
高血压(%)
52.324.8<0.001
47.775.2
糖尿病(%)
18.95.1<0.001
81.194.9
生活方式评分4.0(2.0)6.0(1.0)<0.001
健康生活方式分组(%)
不健康生活方式8.81.8<0.001
中等健康生活方式72.842.7
不健康生活方式18.555.5
), ArticleFig(id=1241342468759802609, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=EN, label=Table 3, caption=

Association of lifestyle scores and healthy lifestyle groupings with NAFLD

, figureFileSmall=null, figureFileBig=null, tableContent=
模型1a模型2b模型3c
OR (95%Cl)POR (95%Cl)POR (95%Cl)P
健康生活方式分组
不健康
中等健康0.343 (0.23-0.51)8.56×10-70.348 (0.23-0.52)3.34×10-90.372 (0.25-0.56)9.15×10-6
健康0.067(0.04-0.10)1.04×10-210.072 (0.05-0.11)3.44×10-210.091 (0.06-0.14)1.50×10-17
生活方式得分0.498 (0.46-0.53)1.45×10-350.498 (0.46-0.53)1.41×10-330.540 (0.50-0.58)1.66×10-27
), ArticleFig(id=1241342468860465914, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241342459574276346, language=CN, label=表3, caption=

生活方式评分以及健康生活方式分组与NAFLD的关联

, figureFileSmall=null, figureFileBig=null, tableContent=
模型1a模型2b模型3c
OR (95%Cl)POR (95%Cl)POR (95%Cl)P
健康生活方式分组
不健康
中等健康0.343 (0.23-0.51)8.56×10-70.348 (0.23-0.52)3.34×10-90.372 (0.25-0.56)9.15×10-6
健康0.067(0.04-0.10)1.04×10-210.072 (0.05-0.11)3.44×10-210.091 (0.06-0.14)1.50×10-17
生活方式得分0.498 (0.46-0.53)1.45×10-350.498 (0.46-0.53)1.41×10-330.540 (0.50-0.58)1.66×10-27
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生活方式评分与非酒精性脂肪肝的关联性研究
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陈颖 , 徐柳红 , 毛盈颖 , 叶丁
现代预防医学 | 疾病预防控制 2024,51(4): 742-747
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现代预防医学 | 疾病预防控制 2024, 51(4): 742-747
生活方式评分与非酒精性脂肪肝的关联性研究
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陈颖, 徐柳红, 毛盈颖, 叶丁
作者信息
  • 浙江中医药大学公共卫生学院,杭州 浙江 310053
  • 陈颖(1999—),女,硕士在读,研究方向:流行病学工作

通讯作者:

叶丁,E-mail:
Associations of lifestyle scores with nonalcoholic fatty liver disease
Ying CHEN, Liu-hong XU, Ying-ying MAO, Ding YE
Affiliations
  • Department of PublicHealth, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310053, China
出版时间: 2024-02-25 doi: 10.20043/j.cnki.MPM.202310283
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目的

基于美国健康与营养调查(NHANES)数据库,探讨生活方式评分与非酒精性脂肪肝(NAFLD)患病之间的关联,为预防和治疗NAFLD提供新思路。

方法

本研究基于2007—2018年的美国NHANES人群数据,通过logistic回归分析评估生活方式对NAFLD的影响。进一步通过分层分析,探讨性别、年龄、种族、婚姻状态、教育程度等不同分层之间的差异。

结果

本研究共纳入4 105名参与者,其中1 284名NAFLD(24.64%),2 821名非NAFLD(75.36%)。研究发现相较于低生活方式评分,生活方式评分中等(OR=0.372,95% CI:0.25~0.56,P=9.15×10-6)和较高(OR=0.091,95% CI:0.06~0.14,P=1.50×10-17)的人群发生NAFLD的风险更低。分层分析显示,该效应在男性和60岁以上人群中更强。

结论

健康生活方式与较低的NAFLD发生风险有关,通过干预生活方式可以有效防治NAFLD。

生活方式评分  /  非酒精性脂肪肝  /  NHANES
Objective

To analyze and explore the association between lifestyle scores and the risk of developing nonalcoholic fatty liver disease (NAFLD) in the United States (US) population, and to provide new ideas for the prevention and treatment of NAFLD.

Methods

The samples of this study were collected from the 2007-2018 US National Health and Nutrition Examination Survey (NHANES) database. Logistic regression analysis was employed to assess the impact of healthy lifestyle and NAFLD. Further stratified analyses were conducted to investigate potential differences across gender, age, ethnicity, marital status, and education levels.

Results

A total of 4 105 participants were included in this study, comprising 1 284 individuals with NAFLD (24.64%) and 2 821 individuals without NAFLD (75.36%). Compared to low lifestyle score, individuals with moderate (OR=0.372, 95% CI: 0.25-0.56, P=9.15×10-6) and high lifestyle score (OR=0.091, 95% CI: 0.06-0.14, P=1.50×10-17) had a lower risk of developing NAFLD. Stratified analyses revealed that this effect was more pronounced among males and individuals aged 60 and above.

Conclusion

Healthy lifestyle is associated with a decreased risk of NAFLD, and improving lifestyle score can be effective in preventing and treating NAFLD.

Lifestyle score  /  NAFLD  /  NHANES
陈颖, 徐柳红, 毛盈颖, 叶丁. 生活方式评分与非酒精性脂肪肝的关联性研究. 现代预防医学, 2024 , 51 (4) : 742 -747 . DOI: 10.20043/j.cnki.MPM.202310283
Ying CHEN, Liu-hong XU, Ying-ying MAO, Ding YE. Associations of lifestyle scores with nonalcoholic fatty liver disease[J]. Modern Preventive Medicine, 2024 , 51 (4) : 742 -747 . DOI: 10.20043/j.cnki.MPM.202310283
非酒精性脂肪性肝病(Non-alcoholic fatty liver disease, NAFLD)是以无酗酒史、肝实质细胞脂质沉积及肝小叶炎症为主要表现的一类临床病理综合征,该疾病由单纯性脂肪肝向非酒精性脂肪性肝炎转变,可进一步发展为肝硬化和肝细胞癌[1]。近年来,NAFLD的发病率不断升高,已严重危害人类的健康。一项系统综述表明,在全球范围内,NAFLD的患病率大约为25%[1],一项前瞻性队列研究表明,美国成年人中NAFLD患病率远高于全球平均水平,约为38%[2]。然而目前尚未有治疗NAFLD的特效药,因此有必要关注潜在的可改变因素,以控制或预防NAFLD的发展。
越来越多的研究提示,一些可改变的生活方式与NAFLD发生风险有关。例如,睡眠不足、久坐和缺乏体育锻炼被认为是肝损伤的主要危险因素,在NAFLD的发生和发展中有着重要作用[3-4]。一项来自17个国家的荟萃分析(531 804名参与者,平均随访时间为13.24年)表明,大约60%的过早死亡可归因于不健康的生活方式因素,包括吸烟、过量饮酒、缺乏身体活动、不良饮食和肥胖[5]。同时,2型糖尿病(T2DM)、高血压患者中NAFLD的发病率高达55%和49.5%,是NAFLD的重要危险因素,与疾病的发生发展密切相关,但在临床实践中通常被忽视[6-7]
上述研究主要探讨了各生活方式因素在NAFLD发生风险中的单独作用,然而研究这些因素的综合作用可能更有助于预测NAFLD的发生风险。因此,本研究利用生活方式评分综合评估各种生活方式风险因素对NAFLD发生的影响,为预防NAFLD的发生和发展提供依据。
研究对象来源于2007—2018年的美国国家健康和营养调查(National Health and Nutrition Examination Survey, NHANES)数据库。NHANES是为了评估美国成年人和儿童健康营养状况,由美国国家健康中心进行的一项横断面调查。NHANES采用了复杂的多阶段抽样设计,先从全国范围内的15个县中随机选择一部分,然后在每个选中的县内随机选择20~24个社区。在选定的社区内随机选择约30户家庭样本,再通过随机抽样确定具体的参与者。这一复杂的抽样设计确保了每次调查的对象都是独立选择的,使得每个研究周期都包含了全新的、代表性的样本。在过去20多年中,NHANES以2年为一个周期,每一周期都调查了一个全新的具有全国代表性的样本,约10 000人,这些人群分布于全国各县。目前NHANES已对外发布11个周期的调查数据,反映了多个时期美国人口的健康和营养特征。该数据库公开可用,已获得伦理审查委员批准,所有调查对象均提供了书面知情同意[8]。本研究选取了2007—2008,2009—2010,2011—2012,2013—2014,2015—2016,2017—2018六个研究周期的数据,共有59 842名参与者,排除了34 770名(58.1%)年龄小于20岁的参与者。由于缺乏腹部超声数据,本研究中使用美国脂肪肝指数(United States Fatty Liver Index, USFLI)进行NAFLD的诊断,如USFLI≥30,则认为该参与者患有NAFLD,USFLI<30则不患NAFLD [9]。排除标准包括:USFLI数据不全(如腰围、胰岛素、葡萄糖等变量缺失,n=20 450),过量饮酒或饮酒数据不全(男性>2杯/天或女性>1杯/天,n=5 767),生活方式因素数据不全(如吸烟、睡眠、饮食等变量缺失,n=1 422),协变量数据不全(种族、教育等变量缺失,n=2 236),病毒性肝炎或肝炎数据缺失(血清乙型肝炎表面抗原阳性和血清丙型肝炎抗体阳性,n=687),妊娠状态或缺失尿检数据(n=103),最后共纳入4 105名参与者作为研究对象。根据USFLI评估(见公式1)[9],将其分为NAFLD组和非NAFLD组。研究对象的筛选流程参见图1
其中X值是通过加权种族、年龄、谷氨酰转移酶(transglutaminase, GGT)、腰围、空腹胰岛素和空腹血糖指标来计算,具体为:-0.807 3*非西班牙裔黑人+0.345 8*墨西哥裔美国人+0.009 3*年龄+0.615 1*loge(GGT)+0.024 9*腰围+1.179 2*loge(空腹胰岛素)+0.824 2*loge(空腹血糖)-14.781 2。其中,若参与对象的种族为“非西班牙裔黑人”或“墨西哥裔美国人”对应变量赋值为1,否则赋值为0。
世界卫生组织发布了名为“Invisiblenumbers:The true extent of noncommunicable diseases and what to do about them”的报告,对全球非传染性疾病的危害、风险因素,以及预防措施等进行了介绍,提出慢性非传染疾病的发生是多种风险因素共同作用的结果,包括吸烟、不健康饮食、饮酒、缺乏运动、高血压、超重或肥胖、高血糖[10]。另外睡眠也越来越成为健康生活方式中不可或缺的因素[11]。目前多项研究探讨了睡眠时间与NAFLD之间的关系,并证明睡眠时间短是NAFLD发病的重要危险因素[3]。因此,本研究确立肥胖、吸烟、饮酒、睡眠时间、饮食、适度体育锻炼,高血压和糖尿病这八个因素为研究变量。生活方式评分为健康生活方式的个数之和,每个健康因素计1分,评分总分范围为0~8分,并将生活方式评分分为三组进行分析,其中得分为0-2的个体为不健康生活方式组,3~5分为中等健康生活方式组,6~8分为健康生活方式组[12]。关于高风险的生活方式定义为:体质量指数(body mass index,BMI)≥30,吸烟≥100支,饮酒≥12杯/去年,睡眠时间<6小时,饮食不健康(回答为一般或较差),没有进行适度体育锻炼,患有高血压,患有糖尿病。反之,则定义为低风险的生活方式。
基本特征包括参与者的性别、年龄、种族、教育水平、婚姻状况等采用个人和家庭问卷调查收集。种族/民族由自我报告信息分为墨西哥美裔、非西班牙裔白人、非西班牙裔黑人、其他西班牙裔和其他种族(包括多个种族)。教育水平根据自我报告信息分为高中以下、高中毕业以及高中以上。婚姻状况根据自我报告分为已婚和未婚。另外通过问卷收集了除肥胖以外的研究变量,如参与者回答了“在你的一生当中至少吸过100支烟?”,“在过去的一年里至少喝了12杯酒?”,“通常在工作日的睡眠时间?”,“一般来说你的整体饮食有多健康?”,“你有没有做任何中等强度的运动、健身或娱乐活动,例如游泳、骑自行车、打高尔夫球或快走,持续至少10分钟,使呼吸或心率有所提高?”,“有医生或卫生专业人员告诉过你患有高血压吗?”,“有医生或卫生专业人员告诉过你患有糖尿病吗?”的问题。肥胖通过BMI指标判定,计算方式为体重(kg)/身高 (m)2
身高、体重、腰围等身体测量学指标由经过统一培训的工作人员使用统一的测量仪器在移动检测中心 (Mobile examination center,MEC)进行检测。葡萄糖、胰岛素、空腹血糖等实验室检测指标由医生在MEC通过静脉穿刺获得,其中空腹血糖要求参与者禁食至少8小时,在现场进行离心处理并-30℃冷冻保存,运送至实验室后通过血生化分析仪进行检测。
数据处理与统计分析使用R 4.3.0和Stata 16.0软件进行,检验水准α=0.05。由于NHANES调查采用复杂分层抽样设计使其具有全国代表性,因此本研究报告的均值、标准误、百分比以及P值均为加权后的值。计量资料在正态分布时以()进行描述,采用t检验进行组间比较;非正态分布时,以中位数(四分位距)进行描述,采用非参数秩和检验进行分析;计数资料以n(%)进行统计描述,利用卡方检验进行组间比较。采用多因素logistic回归分析了生活方式评分与NAFLD发生风险的潜在关联,并针对人口学特征进行了亚组分析,探讨此关联在不同性别、年龄、种族、教育程度、婚姻状态的不同分层之间有无差异。
表1描述了NAFLD组与非NAFLD组基本特征的分布。共有4 105名研究对象纳入分析,其中1 284人(加权百分比31.3%)患有NAFLD,2 821人不患有NAFLD。病例组的加权中位数年龄为59.0(IQR为24.0)岁,男性比例为66.1%,非西班牙裔白人占77.9%,已婚比例为68.1%,高中以上教育水平占66.8%。与对照组相比,NAFLD患者更可能是年纪较大、男性、受教育程度较低、非西班牙裔白人(所有P值均<0.05)。实验室检测数据显示,NAFLD 组葡萄糖、胰岛素、谷丙转氨酶(alanine aminotransferase, ALT)、谷草转氨酶(aspartate transaminase, AST)、谷氨酰转移酶水平均显著升高(均P<0.05),而高密度脂蛋白(high-density lipoprotein, HDL)水平显著下降(P<0.05),见表1
对各生活方式因素在病例组和对照组之间的分布差异进行分析,结果表明,肥胖、睡眠、饮食情况、高血压、糖尿病在非酒精性脂肪肝病例组和对照组间的差异具有统计学意义(P<0.001),未发现饮酒和睡眠时间在组间的统计学差异(P>0.05)见表2
单因素分析表明,与不健康的生活方式组相比,中等健康的生活方式组(OR=0.343,95% CI:0.23~0.51,P=8.56×10-7)、健康的生活方式组(OR=0.067,95% CI:0.04~0.10,P=1.04×10-21)与 NAFLD 发生风险降低有关;校正性别、婚姻和教育水平后,中等健康的生活方式组、健康的生活方式组分别能够降低65.2%(95% CI:48%~77%,P=1.04×10-21)和92.8%(95% CI:89%~95.3%,P=1.04×10-21)NAFLD的发生风险;在模型2的基础上继续校正ALT、AST、HDL后,相对于不健康生活方式组,中等健康的生活方式组(OR=0.372,95% CI:0.25~0.56,P=9.15×10-6)和健康生活方式组(OR=0.091,95% CI:0.06~0.14,P=1.50×10-17)均能够显著降低患NAFLD的风险。另外,单因素分析表明,健康生活方式评分越高,NAFLD 发生风险越低(OR=0.498,95% CI:0.46~0.53,P=1.45×10-35)。校正性别、婚姻和教育水平后,生活方式评分每升高一个单位,NAFLD的发生风险降低50.2%(95% CI:47%~54%,P=1.41×10-33);在模型2的基础上继续校正ALT、AST、HDL,生活方式评分与[LL]NAFLD发生风险呈负相关(OR=0.540,95% CI:0.50~0.58,P=1.66×10-27),见表3
为评估这一关联在不同人群中是否存在异质性,进一步根据人口学特征进行了分层分析。如图2结果所示,我们发现这一关联在性别和年龄中表现出异质性,具体表现为健康生活方式在男性和60岁以上人群中的保护作用更强。
本研究利用NHANES数据库,调查了基于八种生活方式因素的评分与NAFLD的关联。结果表明,与低生活方式评分组相比,中间组的疾病发生风险降低,高分组的风险进一步降低。当进行性别、年龄、种族、婚姻状态等分层分析时,得到了一致的结果。长期的实践经验表明,健康管理的推行对保持和提高亚健康水平、改善生活质量以及降低疾病负担的意义重大[13]。因此,加强个体自身的健康管理,改善不良生活习惯,树立健康和积极向上的生活方式,将会对控制NAFLD的进一步进展起到极大的作用[14]
健康的生活方式可以减轻疾病负担并延长寿命。最近,已有研究探讨了以不吸烟,健康体重,健康饮食和高体力活动为特征的生活方式评分与各种慢性非传染性疾病之间的关系,包括肝脏疾病[15],冠状动脉疾病[16],2型糖尿病[17]。本研究探讨了生活方式评分与NAFLD风险之间的关联,并得到了与以往研究一致的结果。例如,一项针对美国人群的研究表明,较高的生活方式评分与较低的肝纤维化风险有关,并且可以改善肝功能[18]。此外,一项在成年人中进行的横断面研究表明,生活方式评分与肝脂肪变性指数和脂肪肝指数呈负相关[19]。两项针对中国人群的研究报告表明,健康生活方式依从性高可能与NAFLD风险降低有关[20-21]
在分层分析中,本研究发现健康生活方式对NAFLD的保护作用在男性和60岁以上人群中的保护效应更强。出现这样结果的原因可能与不同人群的生活方式有关。相较于女性,男性存在更多不健康的生活习惯,如吸烟、饮酒等[22]。戒烟限酒对NAFLD的保护作用已经被广泛研究和证实,因此如果男性在这些方面采取积极的措施,可能会看到更明显的保护效果[23]。虽然男性可能更容易受益于健康的生活方式,但这并不意味着女性不应该采取类似的措施来降低NAFLD的风险。类似的是,60岁以上的人群有更长时间的机会受到不健康生活方式的影响,如不良的饮食、缺乏运动、肥胖等[24]。这些不良习惯的长期积累可能增加了NAFLD的风险[18]。另外,老年人通常伴随着多种健康问题,如高血压、糖尿病、心血管疾病等[25]。这些疾病与NAFLD有密切关联,老年人因而也更容易受到多重健康问题的影响[6-7]。因此,老年人改变不健康的生活方式可能会更明显地改善他们的健康状况。上述可能解释了健康生活方式因素在这两个人群中呈现出更强的保护效应。
本研究在美国人群中分析了健康生活方式评分与NAFLD的关联,为明确健康生活方式因素对肝病的影响作用提供了新的证据。本研究也存在诸多的不足,首先,横断面研究的设计不能确定确切的因果关系。此外,由于缺乏NAFLD诊断的影像学成像数据,我们未采用金标准用于NAFLD的诊断,因而也存在一定的错分偏倚;NHANES问卷数据主要以自我报告方式收集,因此难以避免回忆偏倚,收集到的数据可能与参与者的实际情况存在一定差异;而且本研究调查对象为美国人群,不同国家之间膳食结构、生活习惯等状况存在一定的差异,因此本研究提供的健康生活方式指标尚不能代表全人群。
综上,本研究的结果进一步强调了健康生活方式在NAFLD预防中的重要性,采取健康的生活方式措施是预防NAFLD的首要手段。因此提高公众对健康生活方式的认知,以及提供支持和资源,将有助于减少NAFLD的疾病负担。然而,未来仍需进一步深入探究生活方式因素与NAFLD发生之间的机制,以及不同人群之间的差异,以制定更加个性化和精准的预防策略。
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doi: 10.20043/j.cnki.MPM.202310283
  • 接收时间:2023-10-20
  • 首发时间:2026-03-19
  • 出版时间:2024-02-25
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  • 收稿日期:2023-10-20
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    浙江中医药大学公共卫生学院,杭州 浙江 310053

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
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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