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Article(id=1240722567762333736, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240722566957027366, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202504014, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1743436800000, receivedDateStr=2025-04-01, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773740911664, onlineDateStr=2026-03-17, pubDate=1760025600000, pubDateStr=2025-10-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773740911664, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773740911664, creator=13701087609, updateTime=1773740911664, 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=3464, endPage=3470, ext={EN=ArticleExt(id=1240722568064323626, articleId=1240722567762333736, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Associations of different physical activity patterns with prevalence of metabolic syndrome: a cross-sectional analysis of NHANES 2011—2020, columnId=1240413921954295836, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods, runingTitle=null, highlight=null, articleAbstract=

Objective This study investigates potential relationships between distinct physical activity patterns and metabolic syndrome (MS) to provide evidence for exercise-based prevention and control of MS. Methods Utilising data from 15 338 US adults in NHANES 2011—2020, participants were stratified into physical activity patterns. Metabolic syndrome (MS) was diagnosed via NCEP-ATP III criteria. Multivariable logistic regression evaluated associations between activity patterns and MS risk. Restricted cubic splines(RCS) were used to model dose-response relationships, and subgroup analyses were conducted. Results Compared with inactive individuals, both weekend warriors (aOR=0.856, 95% CI: 0.736-0.995) and regular exercisers(aOR=0.758, 95% CI: 0.690-0.833) exhibited significant inverse associations with MS risk. RCS analysis demonstrated a progressive reduction in MS risk with increasing total physical activity duration (P≤0.001). Subgroup analyses revealed enhanced protective effects for weekend warriors among adults aged >60 years(aOR=0.679, 95% CI: 0.518-0.887) and males(aOR=0.792, 95% CI: 0.639-0.979). In the regular exercise group, increases in activity duration, intensity, and frequency were significantly associated with lower MS risk. Conclusion This study demonstrates that both regular exercise and weekend warrior physical activity patterns correlate with reduced metabolic syndrome risk, highlighting the importance of physical activity in comprehensive MS prevention and intervention strategies.

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目的 通过探究不同身体活动模式和代谢综合征（metabolic syndrome MS）之间的潜在关系，为运动预防和控制MS提供循证依据。方法 以美国国家健康与营养调查（National Health and Nutrition Examination Suney，NHANES)2011—2020年数据中15 338名成年人为研究对象，根据身体活动水平划分不同模式，采用美国国家胆固醇教育计划成人治疗组第三次报告（NCEP-ATP III）标准诊断MS。应用多因素logistic回归分析不同活动模式与MS风险的关系，采用限制性立方样条（restricted cubic splines,RCS）分析剂量-反应关系并进行亚组分析。结果 与不活跃组相比，周末战士组（aOR=0.856，95%CI:0.736～0.995）和规律运动组（aOR=0.758，95%CI:0.690～0.833）与MS风险呈负向关联；RCS分析显示MS风险随身体活动总时长增加而呈下降趋势（P≤0.001）。亚组分析发现周末战士模式对60岁以上人群（aOR=0.679，95%CI:0.518～0.887）和男性（aOR=0.792，95%CI:0.639～0.979）保护效应更显著；规律运动组中活动时长、强度、频率的增加与MS风险呈显著负相关。结论 本研究表明，规律运动与周末战士身体活动模式均与较低的MS风险相关，强调了身体活动在预防和干预MS综合策略中的重要性。

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唐嘉岭，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=dnWe2KKClIaeZDxOa+2Pmg==, magXml=DiiIsqsXqyd4Oj9JjxAtDg==, pdfUrl=null, pdf=2bsX9kDXxk7AHL2iR/l/1A==, pdfFileSize=970302, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=LvLIb2Yw/nUsE81clTL0Bg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=desFXJcaNpHKidm39MsRiA==, mapNumber=null, authorCompany=null, fund=null, authors=

夏君玫（1972—），女，硕士，教授，研究方向：运动干预慢性病

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夏君玫（1972—），女，硕士，教授，研究方向：运动干预慢性病

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夏君玫（1972—），女，硕士，教授，研究方向：运动干预慢性病

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China Sport Science and Technology, 2021, 57(12): 82-91.(In Chinese), articleTitle=Research progress on the effects of different forms of exercise on essential hypertension, refAbstract=null), Reference(id=1240933504951833524, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, doi=null, pmid=null, pmcid=null, year=2022, volume=34, issue=5, pageStart=555, pageEnd=567, url=null, language=null, rfNumber=[26], rfOrder=34, authorNames=唐韶慨, 耿元文, 林琴琴, journalName=首都体育学院学报, refType=null, unstructuredReference=唐韶慨，耿元文，林琴琴，等.运动调控肌肉、肝脏、脂肪的运动因子的文献计量学分析[J].首都体育学院学报，2022，34（5）：555-567., articleTitle=运动调控肌肉、肝脏、脂肪的运动因子的文献计量学分析, refAbstract=null), Reference(id=1240933505069274043, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, doi=null, pmid=null, pmcid=null, year=2022, volume=34, issue=5, pageStart=555, pageEnd=567, url=null, language=null, rfNumber=[26], rfOrder=35, authorNames=Tang SK, Geng YW, Lin QQ, journalName=Journal of Capital University of Physical Education and Sports, refType=null, unstructuredReference=Tang SK, Geng YW, Lin QQ, et al. Bibliometric analysis of studies related to the regulation of exercise on muscle, liver and lipid exerkines[J]. Journal of Capital University of Physical Education and Sports, 2022, 34(5): 555-567.(In Chinese), articleTitle=Bibliometric analysis of studies related to the regulation of exercise on muscle, liver and lipid exerkines, refAbstract=null), Reference(id=1240933505161548739, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, doi=null, pmid=null, pmcid=null, year=2021, volume=29, issue=10, pageStart=1582, pageEnd=1595, url=null, language=null, rfNumber=[27], rfOrder=36, authorNames=Mengeste AM, Rustan AC, Lund J, journalName=Obesity (Silver Spring, Md.), refType=null, unstructuredReference=Mengeste AM, Rustan AC,Lund J.Skeletal muscle energy metabolism in obesity[J]. Obesity (Silver Spring, Md.), 2021, 29(10): 1582-1595., articleTitle=Skeletal muscle energy metabolism in obesity, refAbstract=null), Reference(id=1240933505299960781, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, doi=null, pmid=null, pmcid=null, year=2024, volume=32, issue=4, pageStart=822, pageEnd=833, url=null, language=null, rfNumber=[28], rfOrder=37, authorNames=Lei L, Li J, Wang W, journalName=Obesity, refType=null, unstructuredReference=Lei L, Li J, Wang W, et al. The associations of "weekend warrior" and regularly active physical activity with abdominal and general adiposity in US adults[J]. Obesity, 2024, 32(4): 822-833., articleTitle=The associations of "weekend warrior" and regularly active physical activity with abdominal and general adiposity in US adults, refAbstract=null), Reference(id=1240933505400624082, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, doi=null, pmid=null, pmcid=null, year=2022, volume=56, issue=7, pageStart=76, pageEnd=83, url=null, language=null, rfNumber=[29], rfOrder=38, authorNames=潘丽英, 马春莲, 谷涌泉, journalName=武汉体育学院学报, refType=null, unstructuredReference=潘丽英， 马春莲， 谷涌泉.6周有氧运动改善不同程度肥胖青少年体质健康的研究[J].武汉体育学院学报，2022，56（7）：76-83., articleTitle=6周有氧运动改善不同程度肥胖青少年体质健康的研究, refAbstract=null), Reference(id=1240933505543230425, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, doi=null, pmid=null, pmcid=null, year=2022, volume=56, issue=7, pageStart=76, pageEnd=83, url=null, language=null, rfNumber=[29], rfOrder=39, authorNames=Pan LY, Ma CL, Gu YQ, journalName=Journal of Wuhan Institute of Physical Education, refType=null, unstructuredReference=Pan LY, Ma CL, Gu YQ. Six week aerobic exercise training improving physical health of adolescents with different degrees of obesity[J]. Journal of Wuhan Institute of Physical Education, 2022, 56(7): 76-83.(In Chinese), articleTitle=Six week aerobic exercise training improving physical health of adolescents with different degrees of obesity, refAbstract=null)], funds=[Fund(id=1240933500883358356, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, awardId=22YJC890029, language=CN, fundingSource=教育部人文社会科学研究一般项目(22YJC890029), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1240933496642916775, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, xref=1., ext=[AuthorCompanyExt(id=1240933496647111080, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, companyId=1240933496642916775, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Physical Education, Central South University, Changsha, Hunan 410083, China), AuthorCompanyExt(id=1240933496655499689, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, companyId=1240933496642916775, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中南大学体育教研部，湖南 长沙 410083)]), AuthorCompany(id=1240933496718414251, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, xref=2., ext=[AuthorCompanyExt(id=1240933496722608556, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, companyId=1240933496718414251, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.华中师范大学体育学院)])], figs=[ArticleFig(id=1240933499293717052, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=EN, label=Figure 1, caption=Flow chart of participant screening, figureFileSmall=0m5Z1omnEO3Mv9q2ww0OHA==, figureFileBig=+TFb13WWhar3QzyqIhuHpA==, tableContent=null), ArticleFig(id=1240933499402768966, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=CN, label=图1, caption=参与者的筛选流程图, figureFileSmall=0m5Z1omnEO3Mv9q2ww0OHA==, figureFileBig=+TFb13WWhar3QzyqIhuHpA==, tableContent=null), ArticleFig(id=1240933499562152527, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=EN, label=Figure 2, caption=RCS of total physical activity duration and metabolic syndrome risk, figureFileSmall=5CiZTFjssV4/KHhG4/cOxA==, figureFileBig=XrKoNTpROYtqOr2hGDAz0Q==, tableContent=null), ArticleFig(id=1240933499629261394, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=CN, label=图2, caption=总身体活动时长与MS风险的限制性立方样条, figureFileSmall=5CiZTFjssV4/KHhG4/cOxA==, figureFileBig=XrKoNTpROYtqOr2hGDAz0Q==, tableContent=null), ArticleFig(id=1240933499708953178, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=EN, label=Table 1, caption=

General characteristics of the study subject ［n（%），（$\bar{x}±s$）]

, figureFileSmall=null, figureFileBig=null, tableContent=
特征总人数MSt/χ2值P值
否是
人口学基本特征15 335(100)10 314(67.3)5 021(32.7)——
年龄（岁）1 041.858<0.001
20～395 051(34.9)4 215(42.2)836(18.4)
40～595 064(36.7)3 290(35.5)1 774(39.6)
≥605 220(28.4)2 809(22.4)2 411(42.0)
性别28.281<0.001
女性8 154(53.6)5 330(53.4)2 824(54.2)
男性7 181(46.4)4 984(46.6)2 197(45.8)
种族106.371<0.001
非西班牙裔白人6 092(68.7)3 959(67.8)2 133(70.7)
非西班牙裔黑人3 566(10.4)2 513(11.0)1 053(8.9)
墨西哥裔美国人1 808(7.2)1 081(6.7)727(8.3)
其他种族3 869(13.7)2 761(14.5)1 108(12.0)
教育程度303.593<0.001
小于9年级965(3.1)507(2.5)458(4.5)
9～11年级（包括12年级但没有文凭）1 526(6.9)940(6.2)586(8.4)
高中毕业或等同学历3 168(20.5)1 989(18.0)1 179(25.9)
大学及以上学历4 696(37.6)3 561(42.1)1 135(27.4)
大学未毕业、副学士学位4 980(31.9)3 317(31.1)1 663(33.8)
贫困收入比74.245<0.001
高收入群体5 353(47.8)3 839(49.7)1 514(43.5)
低收入群体9 982(52.2)6 475(50.3)3 507(56.5)
婚姻状况346.653<0.001
已婚/与伴侣居住8 998(63.6)5 958(62.6)3 040(65.8)
丧偶/离婚/分居3 350(18.0)1 961(15.7)1 389(23.2)
未婚2 987(18.4)2 395(21.7)592(11.0)
吸烟状况136.976<0.001
曾经吸烟3 700(25.8)2 207(22.9)1 493(32.3)
正在吸烟2 543(14.9)1 710(14.9)833(14.9)
从未吸烟9 092(59.3)6 397(62.2)2 695(52.8)
饮酒状况190.912<0.001
曾经饮酒1 598(9.0)854(7.0)744(13.3)
正在饮酒11 676(81.0)8 159(83.6)3 517(75.2)
从未饮酒2 061(10.0)1 301(9.4)760(11.5)
久坐时间（min/d）399.42±2.90392.06±3.98416.03±3.8011.057*<0.001
睡眠时间（h）23.328<0.001
<75 359(30.9)3 521(30.2)1 838(32.3)
7～99 703(67.4)6 636(68.3)3 067(65.4)
>9273(1.7)157(1.5)116(2.3)
热量摄入（kcal）60.433<0.001
Q1(<1 474.5)3 942(22.9)2 493(22.6)1 449(23.5)
Q2(1 474.5～1 905.5)3 927(25.2)2 608(24.8)1 319(26.1)
Q3(1 905.5～2 455)3 820(26.2)2 610(26.5)1 210(25.5)
Q4(>2 455)3 646(25.7)2 603(26.1)1 043(24.8)
高血压2 066.577<0.001
否8 972(63.2)7 336(76.1)1 636(34.3)
是6 363(36.8)2 978(23.9)3 385(65.7)
心血管疾病422.788<0.001
否13 726(91.5)9 598(94.6)4 128(84.3)
是1 609(8.5)716(5.4)893(15.7)
糖尿病2 549.318<0.001
否13 015(88.6)9 805(96.8)3 210(70.0)
是2 320(11.4)509(3.2)1 811(30.0)
肥胖2 047.571<0.001
否9 211(60.8)7 483(73.7)1 728(31.7)
是6 124(39.2)2 831(26.3)3 293(68.3)
调查年份（年）39.963<0.001
2011—20123 150(21.7)2167(21.8)983(21.3)
2013—20143 363(22.1)2236(22.0)1 127(22.5)
2015—20162 956(20.8)1872(19.7)1 084(23.2)
2017—20182 254(17.7)1502(17.9)752(17.3)
2019—20203 612(17.7)2537(18.6)1 075(15.7)
身体活动情况438.589<0.001
不活跃组5 323(28.1)3 079(23.4)2 244(38.8)
活动不足组2 291(15.1)1 455(13.8)836(18.2)
周末战士组1 350(10.2)969(10.7)381(9.1)
规律运动组6 371(46.5)4 811(52.1)1 560(33.9)
), ArticleFig(id=1240933499797033569, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=CN, label=表1, caption=

研究对象的一般特征［n（%），（$\bar{x}±s$）］

, figureFileSmall=null, figureFileBig=null, tableContent=
特征总人数MSt/χ2值P值
否是
人口学基本特征15 335(100)10 314(67.3)5 021(32.7)——
年龄（岁）1 041.858<0.001
20～395 051(34.9)4 215(42.2)836(18.4)
40～595 064(36.7)3 290(35.5)1 774(39.6)
≥605 220(28.4)2 809(22.4)2 411(42.0)
性别28.281<0.001
女性8 154(53.6)5 330(53.4)2 824(54.2)
男性7 181(46.4)4 984(46.6)2 197(45.8)
种族106.371<0.001
非西班牙裔白人6 092(68.7)3 959(67.8)2 133(70.7)
非西班牙裔黑人3 566(10.4)2 513(11.0)1 053(8.9)
墨西哥裔美国人1 808(7.2)1 081(6.7)727(8.3)
其他种族3 869(13.7)2 761(14.5)1 108(12.0)
教育程度303.593<0.001
小于9年级965(3.1)507(2.5)458(4.5)
9～11年级（包括12年级但没有文凭）1 526(6.9)940(6.2)586(8.4)
高中毕业或等同学历3 168(20.5)1 989(18.0)1 179(25.9)
大学及以上学历4 696(37.6)3 561(42.1)1 135(27.4)
大学未毕业、副学士学位4 980(31.9)3 317(31.1)1 663(33.8)
贫困收入比74.245<0.001
高收入群体5 353(47.8)3 839(49.7)1 514(43.5)
低收入群体9 982(52.2)6 475(50.3)3 507(56.5)
婚姻状况346.653<0.001
已婚/与伴侣居住8 998(63.6)5 958(62.6)3 040(65.8)
丧偶/离婚/分居3 350(18.0)1 961(15.7)1 389(23.2)
未婚2 987(18.4)2 395(21.7)592(11.0)
吸烟状况136.976<0.001
曾经吸烟3 700(25.8)2 207(22.9)1 493(32.3)
正在吸烟2 543(14.9)1 710(14.9)833(14.9)
从未吸烟9 092(59.3)6 397(62.2)2 695(52.8)
饮酒状况190.912<0.001
曾经饮酒1 598(9.0)854(7.0)744(13.3)
正在饮酒11 676(81.0)8 159(83.6)3 517(75.2)
从未饮酒2 061(10.0)1 301(9.4)760(11.5)
久坐时间（min/d）399.42±2.90392.06±3.98416.03±3.8011.057*<0.001
睡眠时间（h）23.328<0.001
<75 359(30.9)3 521(30.2)1 838(32.3)
7～99 703(67.4)6 636(68.3)3 067(65.4)
>9273(1.7)157(1.5)116(2.3)
热量摄入（kcal）60.433<0.001
Q1(<1 474.5)3 942(22.9)2 493(22.6)1 449(23.5)
Q2(1 474.5～1 905.5)3 927(25.2)2 608(24.8)1 319(26.1)
Q3(1 905.5～2 455)3 820(26.2)2 610(26.5)1 210(25.5)
Q4(>2 455)3 646(25.7)2 603(26.1)1 043(24.8)
高血压2 066.577<0.001
否8 972(63.2)7 336(76.1)1 636(34.3)
是6 363(36.8)2 978(23.9)3 385(65.7)
心血管疾病422.788<0.001
否13 726(91.5)9 598(94.6)4 128(84.3)
是1 609(8.5)716(5.4)893(15.7)
糖尿病2 549.318<0.001
否13 015(88.6)9 805(96.8)3 210(70.0)
是2 320(11.4)509(3.2)1 811(30.0)
肥胖2 047.571<0.001
否9 211(60.8)7 483(73.7)1 728(31.7)
是6 124(39.2)2 831(26.3)3 293(68.3)
调查年份（年）39.963<0.001
2011—20123 150(21.7)2167(21.8)983(21.3)
2013—20143 363(22.1)2236(22.0)1 127(22.5)
2015—20162 956(20.8)1872(19.7)1 084(23.2)
2017—20182 254(17.7)1502(17.9)752(17.3)
2019—20203 612(17.7)2537(18.6)1 075(15.7)
身体活动情况438.589<0.001
不活跃组5 323(28.1)3 079(23.4)2 244(38.8)
活动不足组2 291(15.1)1 455(13.8)836(18.2)
周末战士组1 350(10.2)969(10.7)381(9.1)
规律运动组6 371(46.5)4 811(52.1)1 560(33.9)
), ArticleFig(id=1240933499918668392, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=EN, label=Table 2, caption=

Relationship between physical activity patterns and metabolic syndrome in adults aged ≥20 years

, figureFileSmall=null, figureFileBig=null, tableContent=
身体活动模式模型1模型2模型3
OR(95%CI)P值aOR(95%CI)P值aOR(95%CI)P值
以不活跃组为参考
不活跃组refrefref
活动不足组0.788(0.713～0.872)<0.0010.836(0.753～0.928)<0.0010.919(0.819～1.032)0.160
周末战士组0.539(0.473～0.614)<0.0010.720(0.627～0.825)<0.0010.856(0.736～0.995)0.044
规律运动组0.445(0.411～0.481)<0.0010.558(0.514～0.606)<0.0010.758(0.690～0.833)<0.001
P for trend<0.001<0.001<0.001
以规律运动为参考
规律运动组refrefref
周末战士组1.213(1.062～1.382)0.0041.291(1.125～1.478)<0.0011.129(0.973～1.308)0.110
活动不足组1.772(1.599～1.963)<0.0011.498(1.346～1.665)<0.0011.212(1.078～1.362)<0.001
不活跃组2.248(2.077～2.432)<0.0011.792(1.650～1.947)<0.0011.319(1.200～1.449)<0.001
P for trend<0.001<0.001<0.001
), ArticleFig(id=1240933500023525998, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=CN, label=表2, caption=

身体活动模式与MS在20岁及以上成年人中的关系

, figureFileSmall=null, figureFileBig=null, tableContent=
身体活动模式模型1模型2模型3
OR(95%CI)P值aOR(95%CI)P值aOR(95%CI)P值
以不活跃组为参考
不活跃组refrefref
活动不足组0.788(0.713～0.872)<0.0010.836(0.753～0.928)<0.0010.919(0.819～1.032)0.160
周末战士组0.539(0.473～0.614)<0.0010.720(0.627～0.825)<0.0010.856(0.736～0.995)0.044
规律运动组0.445(0.411～0.481)<0.0010.558(0.514～0.606)<0.0010.758(0.690～0.833)<0.001
P for trend<0.001<0.001<0.001
以规律运动为参考
规律运动组refrefref
周末战士组1.213(1.062～1.382)0.0041.291(1.125～1.478)<0.0011.129(0.973～1.308)0.110
活动不足组1.772(1.599～1.963)<0.0011.498(1.346～1.665)<0.0011.212(1.078～1.362)<0.001
不活跃组2.248(2.077～2.432)<0.0011.792(1.650～1.947)<0.0011.319(1.200～1.449)<0.001
P for trend<0.001<0.001<0.001
), ArticleFig(id=1240933500149355122, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=EN, label=Table 3, caption=

Relationships between physical activity patterns and metabolic syndrome by age group ［aOR（95% CI）］

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄亚组身体活动模式
不活跃组活动不足组P值周末战士组P值规律运动组P值
20～39岁人群
模型1ref0.945(0.742～1.201)0.6480.726(0.562～0.931)0.0130.521(0.436～0.622)<0.001
模型2ref0.937(0.732～1.193)0.5980.765(0.589～0.989)0.0430.535(0.446～0.642)<0.001
模型3ref0.893(0.671～1.185)0.4360.833(0.619～1.116)0.2240.677(0.547～0.838)<0.001
40～59岁人群
模型1ref0.853(0.719～1.011)0.0680.799(0.643～0.992)0.0430.593(0.518～0.679)<0.001
模型2ref0.874(0.735～1.037)0.1240.801(0.642～0.997)0.0480.596(0.519～0.683)<0.001
模型31.050(0.867～1.272)0.6161.055(0.828～1.342)0.6610.847(0.725～0.989)0.036
60岁以上人群ref
模型1ref0.763(0.653～0.890)<0.0010.587(0.459～0.748)<0.0010.536(0.472～0.610)<0.001
模型2ref0.769(0.658～0.898)<0.0010.600(0.469～0.766)<0.0010.543(0.477～0.618)<0.001
模型3ref0.828(0.698～0.982)0.0300.679(0.518～0.887)0.0050.735(0.635～0.850)<0.001
), ArticleFig(id=1240933500224852599, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=CN, label=表3, caption=

不同年龄组的身体活动模式与MS的关系［aOR（95%CI）］

, figureFileSmall=null, figureFileBig=null, tableContent=
年龄亚组身体活动模式
不活跃组活动不足组P值周末战士组P值规律运动组P值
20～39岁人群
模型1ref0.945(0.742～1.201)0.6480.726(0.562～0.931)0.0130.521(0.436～0.622)<0.001
模型2ref0.937(0.732～1.193)0.5980.765(0.589～0.989)0.0430.535(0.446～0.642)<0.001
模型3ref0.893(0.671～1.185)0.4360.833(0.619～1.116)0.2240.677(0.547～0.838)<0.001
40～59岁人群
模型1ref0.853(0.719～1.011)0.0680.799(0.643～0.992)0.0430.593(0.518～0.679)<0.001
模型2ref0.874(0.735～1.037)0.1240.801(0.642～0.997)0.0480.596(0.519～0.683)<0.001
模型31.050(0.867～1.272)0.6161.055(0.828～1.342)0.6610.847(0.725～0.989)0.036
60岁以上人群ref
模型1ref0.763(0.653～0.890)<0.0010.587(0.459～0.748)<0.0010.536(0.472～0.610)<0.001
模型2ref0.769(0.658～0.898)<0.0010.600(0.469～0.766)<0.0010.543(0.477～0.618)<0.001
模型3ref0.828(0.698～0.982)0.0300.679(0.518～0.887)0.0050.735(0.635～0.850)<0.001
), ArticleFig(id=1240933500342293116, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=EN, label=Table 4, caption=

Relationships between physical activity patterns and metabolic syndrome by sex

, figureFileSmall=null, figureFileBig=null, tableContent=
主变量男性组aOR(95%CI)P值女性组aOR(95%CI)P值
模型1
不活跃组refref
活动不足组0.897(0.767～1.048)0.1700.720(0.630～0.822)<0.001
周末战士组0.507(0.424～0.605)<0.0010.622(0.510～0.757)<0.001
规律运动组0.435(0.386～0.490)<0.0010.465(0.418～0.517)<0.001
模型2
不活跃组refref
活动不足组0.952(0.809～1.119)0.5540.759(0.662～0.871)<0.001
周末战士组0.677(0.560～0.817)<0.0010.790(0.643～0.968)0.024
规律运动组0.560(0.493～0.634)<0.0010.564(0.505～0.631)<0.001
模型3
不活跃组refref
活动不足组0.997(0.829～1.199)0.9760.877(0.754～1.019)0.087
周末战士组0.792(0.639～0.979)0.0320.968(0.773～1.208)0.773
规律运动组0.711(0.615～0.823)<0.0010.812(0.717～0.921)<0.001
), ArticleFig(id=1240933500434567810, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=CN, label=表4, caption=

不同性别分组下身体活动模式与MS的关系

, figureFileSmall=null, figureFileBig=null, tableContent=
主变量男性组aOR(95%CI)P值女性组aOR(95%CI)P值
模型1
不活跃组refref
活动不足组0.897(0.767～1.048)0.1700.720(0.630～0.822)<0.001
周末战士组0.507(0.424～0.605)<0.0010.622(0.510～0.757)<0.001
规律运动组0.435(0.386～0.490)<0.0010.465(0.418～0.517)<0.001
模型2
不活跃组refref
活动不足组0.952(0.809～1.119)0.5540.759(0.662～0.871)<0.001
周末战士组0.677(0.560～0.817)<0.0010.790(0.643～0.968)0.024
规律运动组0.560(0.493～0.634)<0.0010.564(0.505～0.631)<0.001
模型3
不活跃组refref
活动不足组0.997(0.829～1.199)0.9760.877(0.754～1.019)0.087
周末战士组0.792(0.639～0.979)0.0320.968(0.773～1.208)0.773
规律运动组0.711(0.615～0.823)<0.0010.812(0.717～0.921)<0.001
), ArticleFig(id=1240933500522648198, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=EN, label=Table 5, caption=

Effects of duration, intensity, and frequency of different physical activity patterns on metabolic syndrome

, figureFileSmall=null, figureFileBig=null, tableContent=
主变量模型1模型2模型3
OR(95%CI)P值aOR(95%CI)P值aOR(95%CI)P值
身体活动时长（min/d）
周末战士组
Q1refrefref
Q20.673(0.447～1.022)0.0600.767(0.500～1.186)0.2270.738(0.455～1.204)0.220
Q30.817(0.532～1.264)0.3600.960(0.613～1.516)0.8600.853(0.512～1.430)0.544
Q40.670(0.441～1.026)0.0630.812(0.521～1.274)0.3600.749(0.449～1.257)0.271
规律运动组
Q1refrefref
Q20.678(0.553～0.833)<0.0010.734(0.594～0.909)0.0040.762(0.602～0.967)0.025
Q30.575(0.466～0.712)<0.0010.675(0.542～0.842)<0.0010.633(0.495～0.812)<0.001
Q40.505(0.406～0.629)<0.0010.679(0.539～0.856)0.0010.567(0.436～0.740)<0.001
身体活动强度水平（%）
周末战士组
≤25%refrefref
26%～50%0.930(0.671～1.288)0.6601.006(0.716～1.413)0.9720.986(0.674～ 1.441)0.941
51%～75%1.002(0.716～1.402)0.9901.092(0.769～1.551)0.6220.977(0.655～ 1.454)0.907
>75%0.843(0.603～1.176)0.3150.982(0.689～1.400)0.9220.955(0.632～ 1.441)0.825
规律运动组
≤25%refrefref
26%～50%0.767(0.654～0.899)0.0010.853(0.724～1.005)0.0570.905(0.753～1.087)0.288
51%～75%0.736(0.630～0.860)<0.0010.849(0.722～0.998)0.0470.775(0.645～0.931)0.007
>75%0.642(0.547～0.752)<0.0010.842(0.711～0.997)0.0470.702(0.575～0.857)<0.001
身体活动频率（d/周）
周末战士组
1refrefref
21.028(0.801～1.324)0.8290.946(0.728～1.232)0.6780.920(0.689～ 1.231)0.574
规律运动组
3～4refrefref
≥50.773(0.688～0.869)<0.0010.760(0.674～0.858)<0.0010.863(0.754～0.988)0.033
), ArticleFig(id=1240933500644283019, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240722567762333736, language=CN, label=表5, caption=

不同身体活动模式的时间、强度、频率对MS的影响

, figureFileSmall=null, figureFileBig=null, tableContent=
主变量模型1模型2模型3
OR(95%CI)P值aOR(95%CI)P值aOR(95%CI)P值
身体活动时长（min/d）
周末战士组
Q1refrefref
Q20.673(0.447～1.022)0.0600.767(0.500～1.186)0.2270.738(0.455～1.204)0.220
Q30.817(0.532～1.264)0.3600.960(0.613～1.516)0.8600.853(0.512～1.430)0.544
Q40.670(0.441～1.026)0.0630.812(0.521～1.274)0.3600.749(0.449～1.257)0.271
规律运动组
Q1refrefref
Q20.678(0.553～0.833)<0.0010.734(0.594～0.909)0.0040.762(0.602～0.967)0.025
Q30.575(0.466～0.712)<0.0010.675(0.542～0.842)<0.0010.633(0.495～0.812)<0.001
Q40.505(0.406～0.629)<0.0010.679(0.539～0.856)0.0010.567(0.436～0.740)<0.001
身体活动强度水平（%）
周末战士组
≤25%refrefref
26%～50%0.930(0.671～1.288)0.6601.006(0.716～1.413)0.9720.986(0.674～ 1.441)0.941
51%～75%1.002(0.716～1.402)0.9901.092(0.769～1.551)0.6220.977(0.655～ 1.454)0.907
>75%0.843(0.603～1.176)0.3150.982(0.689～1.400)0.9220.955(0.632～ 1.441)0.825
规律运动组
≤25%refrefref
26%～50%0.767(0.654～0.899)0.0010.853(0.724～1.005)0.0570.905(0.753～1.087)0.288
51%～75%0.736(0.630～0.860)<0.0010.849(0.722～0.998)0.0470.775(0.645～0.931)0.007
>75%0.642(0.547～0.752)<0.0010.842(0.711～0.997)0.0470.702(0.575～0.857)<0.001
身体活动频率（d/周）
周末战士组
1refrefref
21.028(0.801～1.324)0.8290.946(0.728～1.232)0.6780.920(0.689～ 1.231)0.574
规律运动组
3～4refrefref
≥50.773(0.688～0.869)<0.0010.760(0.674～0.858)<0.0010.863(0.754～0.988)0.033
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不同身体活动模式与代谢综合征患病风险的横断面分析——基于NHANES 2011—2020
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夏君玫 1 , 郝宏弢 1 , 梁计陵 1 , 刘宇航 2 , 高思垚 1 , 唐嘉岭 1
现代预防医学 | 流行病与统计方法 2025,52(19): 3464-3470
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现代预防医学 | 流行病与统计方法 2025, 52(19): 3464-3470
不同身体活动模式与代谢综合征患病风险的横断面分析——基于NHANES 2011—2020
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夏君玫1, 郝宏弢1, 梁计陵1, 刘宇航2, 高思垚1, 唐嘉岭1
作者信息
  • 1.中南大学体育教研部，湖南 长沙 410083
  • 2.华中师范大学体育学院

    • 夏君玫（1972—），女，硕士，教授，研究方向：运动干预慢性病

通讯作者:

唐嘉岭，E-mail:
Associations of different physical activity patterns with prevalence of metabolic syndrome: a cross-sectional analysis of NHANES 2011—2020
Jun-mei XIA1, Hong-tao HAO1, Ji-ling LIANG1, Yu-hang LIU2, Si-yao GAO1, Jia-ling TANG1
Affiliations
  • Department of Physical Education, Central South University, Changsha, Hunan 410083, China
出版时间: 2025-10-10 doi: 10.20043/j.cnki.MPM.202504014
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摘要
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目的 通过探究不同身体活动模式和代谢综合征（metabolic syndrome MS）之间的潜在关系，为运动预防和控制MS提供循证依据。方法 以美国国家健康与营养调查（National Health and Nutrition Examination Suney，NHANES)2011—2020年数据中15 338名成年人为研究对象，根据身体活动水平划分不同模式，采用美国国家胆固醇教育计划成人治疗组第三次报告（NCEP-ATP III）标准诊断MS。应用多因素logistic回归分析不同活动模式与MS风险的关系，采用限制性立方样条（restricted cubic splines,RCS）分析剂量-反应关系并进行亚组分析。结果 与不活跃组相比，周末战士组（aOR=0.856，95%CI:0.736～0.995）和规律运动组（aOR=0.758，95%CI:0.690～0.833）与MS风险呈负向关联；RCS分析显示MS风险随身体活动总时长增加而呈下降趋势（P≤0.001）。亚组分析发现周末战士模式对60岁以上人群（aOR=0.679，95%CI:0.518～0.887）和男性（aOR=0.792，95%CI:0.639～0.979）保护效应更显著；规律运动组中活动时长、强度、频率的增加与MS风险呈显著负相关。结论 本研究表明，规律运动与周末战士身体活动模式均与较低的MS风险相关，强调了身体活动在预防和干预MS综合策略中的重要性。

身体活动  /  代谢综合征  /  横断面研究

Objective This study investigates potential relationships between distinct physical activity patterns and metabolic syndrome (MS) to provide evidence for exercise-based prevention and control of MS. Methods Utilising data from 15 338 US adults in NHANES 2011—2020, participants were stratified into physical activity patterns. Metabolic syndrome (MS) was diagnosed via NCEP-ATP III criteria. Multivariable logistic regression evaluated associations between activity patterns and MS risk. Restricted cubic splines(RCS) were used to model dose-response relationships, and subgroup analyses were conducted. Results Compared with inactive individuals, both weekend warriors (aOR=0.856, 95% CI: 0.736-0.995) and regular exercisers(aOR=0.758, 95% CI: 0.690-0.833) exhibited significant inverse associations with MS risk. RCS analysis demonstrated a progressive reduction in MS risk with increasing total physical activity duration (P≤0.001). Subgroup analyses revealed enhanced protective effects for weekend warriors among adults aged >60 years(aOR=0.679, 95% CI: 0.518-0.887) and males(aOR=0.792, 95% CI: 0.639-0.979). In the regular exercise group, increases in activity duration, intensity, and frequency were significantly associated with lower MS risk. Conclusion This study demonstrates that both regular exercise and weekend warrior physical activity patterns correlate with reduced metabolic syndrome risk, highlighting the importance of physical activity in comprehensive MS prevention and intervention strategies.

Physical activity  /  Metabolic syndrome  /  Cross-sectional analysis
夏君玫, 郝宏弢, 梁计陵, 刘宇航, 高思垚, 唐嘉岭. 不同身体活动模式与代谢综合征患病风险的横断面分析——基于NHANES 2011—2020. 现代预防医学, 2025 , 52 (19) : 3464 -3470 . DOI: 10.20043/j.cnki.MPM.202504014
Jun-mei XIA, Hong-tao HAO, Ji-ling LIANG, Yu-hang LIU, Si-yao GAO, Jia-ling TANG. Associations of different physical activity patterns with prevalence of metabolic syndrome: a cross-sectional analysis of NHANES 2011—2020[J]. Modern Preventive Medicine, 2025 , 52 (19) : 3464 -3470 . DOI: 10.20043/j.cnki.MPM.202504014
正文
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代谢综合征（metabolic syndrome，MS）是一组相互关联的代谢异常的集合，也是多种慢性疾病的前兆[1]。随着人口老龄化和超重肥胖等情况的加剧，MS及其继发疾病已成为危害人类健康的重大公共卫生问题[2]。近年来MS患病呈上升趋势，运动量减少、长期久坐、不良饮食习惯是MS患病率升高的主要原因[3]。目前全球约超10亿人患有MS，中国老年人MS合并患病率高达23.9%，女性合并患病率明显高于男性[4-5]。因此，防控MS对保障人民群众生命健康具有重要意义。
研究表明，增加身体活动与低MS患病率存在显著关联，其中有氧联合抗阻运动是MS相关健康问题最有效的运动类型之一[6-7]。除运动的种类、强度外，时长的增加也与MS的患病风险呈负向关系[8]。世界卫生组织[9]和我国身体活动指南[10]均推荐65岁以下成年人每周进行至少150 min的中高强度身体活动（moderate-to-vigorous physical activity，MVPA）。但在快节奏的现代社会生活中，许多人受诸多因素影响，无法定期完成推荐的身体活动量，只能选择在每周1～2 d内集中进行锻炼，这些人群被称为“周末战士”[11]。为了解包括周末战士在内不同锻炼频率的身体活动模式与MS的潜在联系，本文利用美国国家健康与营养调查（National Health and Nutrition Examination Survey，NHANES）数据库进行研究，以期对MS的预防提供更多科学依据。
1　对象与方法
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1.1　研究人群
研究采用NHANES数据库2011—2020年调查周期中共计43 395名成年参与者的数据。排除标准：（1）年龄<20岁；（2）缺失身体活动数据；（3）缺失MS及协变量信息。最终共纳入15 335例参与者数据。见图1。
1.2　研究变量
1.2.1　自变量定义与赋值
自变量为身体活动模式（physical activity pattern），使用NHANES中的标准化问卷对身体活动（physical activity）进行评估，并综合考量了活动频率（每周次数）和持续时间（单次时长）。其中1 min高强度活动被等效为2 min中等强度活动，合并为MVPA，因此每周总MVPA时长可以通过公式计算：2×高强度身体活动+中等强度身体活动[12]。根据每周MVPA频次与总时长，自变量赋值如下所示：
不活跃组：没有报告每周MVPA，赋值= 0；
活动不足组：MVPA<150 min，赋值= 1；
周末战士组：MVPA≥150 min，1～2次运动中完成，赋值= 2；
规律运动组：MVPA≥150 min，≥3次运动完成，赋值= 3。
1.2.2　因变量定义与赋值
因变量为MS，应用美国国家胆固醇教育计划成人治疗组第三次报告（NCEP-ATP III）的标准判定：（1）男性腰围>102 cm或女性>88 cm；（2）空腹血糖≥100 mg/dl；（3）甘油三酯≥150 mg/dl；（4）男性高密度脂蛋白胆固醇（HDL-C）<40 mg/dl或女性<50 mg/dl；（5）收缩压≥130 mmHg和/或舒张压≥85 mmHg。满足≥3项即定义为患病[13]。赋值方式：MS患病=1，MS未患病=0。
1.3　协变量评估
研究纳入的协变量包括年龄、种族、性别、教育水平、婚姻状况、家庭贫困收入比、吸烟状况、饮酒状况、总热量摄入、久坐时间、睡眠时间、高血压、糖尿病、肥胖、心血管疾病。
1.4　统计学分析
研究使用R 4.3.2进行分析处理。根据MS状态进行人口学特征描述，连续变量采用t检验进行比较，以（均数±标准误）表示；分类变量采用χ2检验，以频数（%）表示；应用限制性立方样条（restricted cubic spline，RCS）分析身体活动时长与MS。构建多因素logistic模型估算不同身体活动模式与MS之间的比值比（odds ratio, OR）及95%置信区间（confidence interval, CI），以探讨二者之间的关系，logistic回归模型设置如下：模型1仅含自变量；模型2在模型1基础上调整年龄、种族、性别；模型3在模型2的基础上进一步调整了剩余协变量。
并针对性别、年龄、和不同模式的时间、强度、频率进行亚组分析，所有统计检验均为双侧检验，检验水准α=0.05。
2　结果
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2.1　研究人群的基本特征
如表1所示，在符合研究的15 335名参与者中MS的患病率约为32.7%，男性患病率低于女性，60岁以上人群患病率最高，为42.0%（P≤0.001），共有7 721人（56.7%）符合指南推荐的运动量，其中1 042人（10.2%）为周末战士人群，6 371人（46.5%）为规律运动人群。此外高血压患者和肥胖人群的患病率较高（65.7%～68.3%，P≤0.001）。
2.2　全人群中身体活动模式对MS的影响
多因素logistic回归模型结果如表2所示，周末战士组（aOR=0.856，95%CI：0.736～0.995）和规律运动组（aOR=0.758，95%CI：0.690～0.833）都与MS患病呈负相关；规律运动组患病率更低且更显著，而在活动不足组（aOR=0.919，95%CI：0.819～1.032）中未观察到这种关系。将规律运动组作为参照组则未观察到周末战士组和规律运动组与MS之间存在显著关联（aOR=1.129，95%CI：0.973～1.308），而活动不足组（aOR=1.212，95%CI：1.078～1.362）和不活跃组（aOR=1.319，95%CI：1.200～1.449）出现MS的风险较高。
2.3　不同年龄中身体活动模式对MS的影响
将研究人群以20岁为间隔分组，进行亚组分析后发现：对于60岁以上人群，周末战士组与MS患病率呈现显著负相关系（aOR=0.679，95%CI：0.518～0.887），而在其他年龄段的周末战士组中并未观察到这一现象。见表3。
2.4　不同性别中身体活动模式对MS的影响
按照性别进行亚组分析后发现：相较于不运动或缺乏运动的人群，规律运动组中所有性别群体的MS患病率均较低，但在周末战士组中，只有男性群体中的周末战士组与MS的患病呈负相关（aOR=0.792，95%CI：0.639～0.979），女性中并未观察到统计学关联（aOR=0.968，95%CI：0.773～1.208）。见表4。
2.5　不同身体活动模式中时长、强度、频率对MS的影响
图2结果显示，MS的风险随身体活动总时长的增加而呈下降趋势（P总趋势≤0.001；P非线性≤0.001）；为进一步探讨周末战士和规律运动两种身体活动模式与MS的关系并分析结果的合理性，研究将两组人群的身体活动按照时长、强度、频率进行了亚组分析。结果表明，在三个层面中，规律运动的身体活动模式与MS之间有着显著的负向关系。受限于运动频率过低的绝对影响，周末战士人群的结果虽未达到统计学的显著性水平，但依旧在身体活动总时长的层面与MS之间显示出微弱的负向关系。见表5。
3　讨论
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本研究的主要目的是探讨以周末战士为主不同身体活动模式与MS患病风险之间的关联。结果显示，与不运动人群相比，周末战士和规律运动的身体活动模式均与较低患病率有显著关联。亚组分析的结果显示，在男性和60岁以上的人群中，周末战士身体活动模式与MS的低患病率仍存在显著关联；同时更长时间、更大强度的MVPA与MS的低患病率关联更加明显。
充分的身体活动是MS的保护因素，只要达到推荐的每周150 min中等强度身体活动水平就可以有效降低MS患病率[6,14]。一项涉及我国20 502名农村成年人研究发现：与不活跃的参与者相比，周末战士人群患MS、糖尿病和高血压的风险较低[15]，这与本研究的结果一致。另一项利用英国生物银行样本库中89 573名参与者队列数据的研究发现：与每周规律运动的人群相比，周末战士身体活动模式同样可以降低心房颤动、心肌梗死、心力衰竭和中风等不良事件发生的风险[16]。因此，研究推断周末战士人群患MS风险较低的原因可能是与规律运动的模式具有相似的健康效应。
有研究发现，身体活动可以改善MS的异常组分[17-18]。高血压是MS中最常见的组分，同时也是MS与心血管疾病联系最为紧密的组分[19-20]。而身体活动会增加人体的血流量，促进组织中儿茶酚胺的清除，减弱肌肉交感神经活动的增加以及神经血管传导的钝化现象从而降低血压[21]。有研究对自发性高血压大鼠进行8周游泳训练后发现，大鼠的血管紧张素（1-7）和MAS受体的表达水平均有所上调[22]。此外，有研究发现，休闲时间身体活动与高血压风险之间存在负相关，在这一条件下满足最低身体活动水平的个体患高血压的风险平均降低6%，且随着时长与强度的增长，该风险会进一步下降[23]。另一项研究在对110万名英国女性进行研究后发现，每日进行身体活动的女性比每周进行2～3次身体活动的女性罹患冠心病、脑血管病及静脉血栓栓塞的风险更低[24]。因此，在保证安全的前提下增加运动强度会产生更大的血压降幅[25]。
肥胖也是MS的常见组分之一。有研究证实，定期进行身体活动，尤其是进行抗阻运动，可以增加人体肌肉量，从而提高基础代谢率，更高的基础代谢率意味着安静时可以燃烧更多的热量，而有氧运动可以调控脂肪运动因子表达进而改善胰岛素敏感性[26]，耐力运动则可增加骨骼肌的脂肪酸运输能力并提高线粒体脂肪酸氧化能力，从而促进膳食脂肪从储存向氧化的转变[27]。一项有关周末战士和规律运动人群身体活动与腹部和全身肥胖关联的研究显示，在身体活动总量相同的情况下，每周进行1～2次锻炼的参与者往往具有较低的腹部脂肪、较小腰围和较少的全身脂肪量[28]。为此有学者针对运动干预的周期、强度进行研究后发现仅3周时长的有氧运动就能显著下调中度和重度肥胖青少年血脂、TG和胰岛素抵抗指数等指标[29]。
综上所述，周末战士身体活动模式具有与规律运动身体活动模式相似的健康益处，增加身体活动MS的常见异常组分有着较好的改善效果。
本研究发现，不论每周锻炼的频次如何，只要达到推荐的身体活动量就可以降低MS的风险。建议身体情况允许的人群应更加积极地参与日常体育运动，进行至少每周150 min的中高强度有氧运动，并有目的增加运动强度。如果无法进行规律运动选择周末战士的身体活动模式也是一种可行的运动方案。
本文也存在一定局限性，由于本文受横断面研究设计的限制，无法得出变量之间的因果关系。此外，身体活动的数据依赖于自我报告，难以避免参与者对实际情况的夸大或低估。因此，未来研究应采用电子设备精确测量身体活动量，深入研究身体活动模式对MS或其他慢性疾病的干预效果。
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2025年第52卷第19期
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doi: 10.20043/j.cnki.MPM.202504014
  • 接收时间：2025-04-01
  • 首发时间：2026-03-17
  • 出版时间：2025-10-10
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教育部人文社会科学研究一般项目(22YJC890029)
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    1.中南大学体育教研部，湖南 长沙 410083
    2.华中师范大学体育学院

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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光柄菇属 Pluteus 5 2.39
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